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Volume 14, January
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Actuators, Volume 14, Issue 2 (February 2025) – 23 articles

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30 pages, 2771 KiB  
Article
A Symmetrical RRPRR Robust Coupling for Crossed Axes Transmission
by Toma-Marian Ciocirlan, Stelian Alaci, Florina-Carmen Ciornei, Ionut-Cristian Romanu and Ioan Doroftei
Actuators 2025, 14(2), 64; https://doi.org/10.3390/act14020064 - 29 Jan 2025
Viewed by 199
Abstract
A new coupling solution for transmitting the rotation motion between two shafts with crossed axes is proposed. Based on structural considerations, a planar (P) pair is introduced into the structure of the mechanism, presenting the advantage of reduced costs due to the constructive [...] Read more.
A new coupling solution for transmitting the rotation motion between two shafts with crossed axes is proposed. Based on structural considerations, a planar (P) pair is introduced into the structure of the mechanism, presenting the advantage of reduced costs due to the constructive and manufacturing simplicity and to high reliability. The proposed mechanism is of the RRPRR type, and the structural symmetry simplifies substantially the construction of the mechanism. The constructive parameters of the mechanism are the angle and distance between the driving and driven shaft and also the length of the common normal between the axes of driving and driven revolute (R) pairs, and the axes of the revolute pairs of the coupling chain, respectively. Due to the presence of the planar pair, the Hartenberg–Denavit method of homogenous operators is not applicable. The kinematic analysis for a specified motion of the driving element requires two stages: finding the relative motions from the revolute pairs and the motions from the planar pair. The RRPRR transmission is analysed for geometrical asymmetrical and symmetrical cases; the latter is more convenient and the design principles are presented. Concerning the dimensional optimization, it is found to be a methodology for ensuring that the transmission ratio of the mechanism can be maintained within a stipulated range. Based on the kinematical calculus and geometrical optimization, the mechanism was designed and manufactured. Full article
(This article belongs to the Section High Torque/Power Density Actuators)
28 pages, 3329 KiB  
Article
Development of a Basilar Membrane-Inspired Mechanical Spectrum Analyzer Using Metastructures for Enhanced Frequency Selectivity
by Shantanu H. Chavan and Vijaya V. N. Sriram Malladi
Actuators 2025, 14(2), 63; https://doi.org/10.3390/act14020063 - 29 Jan 2025
Viewed by 193
Abstract
This study introduces a mechanical spectrum analyzer (MSA) inspired by the tonotopic organization of the basilar membrane (BM), designed to achieve two critical features. First, it replicates the traveling-wave behavior of the BM, characterized by energy dissipation without reflections at the boundaries. Second, [...] Read more.
This study introduces a mechanical spectrum analyzer (MSA) inspired by the tonotopic organization of the basilar membrane (BM), designed to achieve two critical features. First, it replicates the traveling-wave behavior of the BM, characterized by energy dissipation without reflections at the boundaries. Second, it enables the physical encoding of the wave energy into distinct spectral components. Moving beyond the conventional focus on metamaterial design, this research investigates wave propagation behavior and energy dissipation within metastructures, with particular attention to how individual unit cells absorb energy. To achieve these objectives, a metastructural design methodology is employed. Experimental characterization of metastructure samples with varying numbers of unit cells is performed, with reflection and absorption coefficients used to quantify energy absorption and assess bandgap quality. Simulations of a basilar membrane-inspired structure incorporating multiple sets of dynamic vibration resonators (DVRs) demonstrate frequency selectivity akin to the natural BM. The design features four types of DVRs, resulting in stepped bandgaps and enabling the MSA to function as a frequency filter. The findings reveal that the proposed MSA effectively achieves frequency-selective wave propagation and broad bandgap performance. The quantitative analysis of energy dissipation, complemented by qualitative demonstrations of wave behavior, highlights the potential of this metastructural approach to enhance frequency selectivity and improve sound processing. These results lay the groundwork for future exploration of 2D metastructures and applications such as energy harvesting and advanced wave filtering. Full article
(This article belongs to the Special Issue Actuator Technology for Active Noise and Vibration Control)
16 pages, 6815 KiB  
Article
Investigating the Power Extraction of Applying Hybrid Pitching Motion on a Wing with Leading and Trailing Flaps
by Suleiman Saleh and Chang-Hyun Sohn
Actuators 2025, 14(2), 62; https://doi.org/10.3390/act14020062 - 27 Jan 2025
Viewed by 366
Abstract
This research utilized a hybrid trajectory on a wing incorporating a dual flap with the goal of enhancing performance. The hybrid profiles initiate with a non-sinusoidal pattern during the interval 0.0 ≤ t/T ≤ 0.25, evolving toward a sinusoidal pattern within the range [...] Read more.
This research utilized a hybrid trajectory on a wing incorporating a dual flap with the goal of enhancing performance. The hybrid profiles initiate with a non-sinusoidal pattern during the interval 0.0 ≤ t/T ≤ 0.25, evolving toward a sinusoidal pattern within the range 0.25 < t/T ≤ 0.5. Similarly, the hybrid motion follows a non-sinusoidal pattern in the range 0.5 < t/T ≤ 0.75, before shifting back to a sinusoidal pattern within the range 0.75 < t/T ≤ 1.0. The effectiveness of using a hybrid trajectory on a wing with leading and trailing flaps in enhancing the energy harvesting performance is examined through numerical simulations. The results demonstrate that hybrid trajectories applied to a two-flap wing configuration outperform a single flat plate and a wing with leading and trailing flaps both operating under a sinusoidal trajectory. The wing length spans from 45% to 55%, with the leading flap length ranging from 25% to 35%. The trailing flap lengths adjust accordingly to ensure the combined total matches the flat plate’s full length, which is 100%. The wing pitch angle was fixed at 85° while the leading flap’s pitch angle varied between 40° and 55° and the pitch angle of the trailing flap ranged from 0° to 20°. The findings reveal that utilizing hybrid motion on a wing fitted with leading and trailing flaps notably improves power output in comparison to configurations with either one plate or three plates. The power output is achieved at particular dimensions: a leading flap length of 30%, a wing length of 55%, and a trailing flap length of 15%. The corresponding pitch angles are 50° for the leading flap, 85° for the wing, and 10° for the trailing flap. The aforementioned configuration results in a 34.06% increase in output power in comparison to one plate. The maximum efficiency for this setup reaches 44.21%. This underscores the superior performance of hybrid trajectories over sinusoidal trajectories in enhancing energy extraction performance. Full article
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<p>Illustrations of a wing using two flaps.</p>
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<p>Kinematics of (<b>a</b>) a single flat plate; (<b>b</b>) a wing with leading and trailing flaps.</p>
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<p>Pitch angle profiles: (<b>a</b>) sinusoidal; (<b>b</b>) non-sinusoidal; (<b>c</b>) hybrid motions.</p>
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<p>Shows (<b>a</b>) computational domain; (<b>b</b>) sub-region; and (<b>c</b>) closeup view.</p>
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<p>Analysis of (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">L</mi> </mrow> </msub> </mrow> </semantics></math> [<a href="#B57-actuators-14-00062" class="html-bibr">57</a>] and (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">p</mi> <mi mathvariant="normal">l</mi> </mrow> </msub> </mrow> </semantics></math> [<a href="#B57-actuators-14-00062" class="html-bibr">57</a>] in turbulent flow.</p>
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<p>The calculated results for (<b>a</b>) total power coefficient and (<b>b</b>) efficiency for Cases 2 and 4.</p>
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<p>Comparison of (<b>a</b>) pushing force coefficient, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">L</mi> </mrow> </msub> </mrow> </semantics></math>(t); (<b>b</b>) pushing power coefficient, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">p</mi> <mi mathvariant="normal">l</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>c</b>) moment coefficient, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">M</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>d</b>) moment power coefficient, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">p</mi> <mi mathvariant="normal">m</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>e</b>) total power coefficient, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">p</mi> <mi mathvariant="normal">t</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Comparison of (<b>a</b>) pushing force coefficient, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">L</mi> </mrow> </msub> </mrow> </semantics></math>(t); (<b>b</b>) pushing power coefficient, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">p</mi> <mi mathvariant="normal">l</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>c</b>) moment coefficient, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">M</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>d</b>) moment power coefficient, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">p</mi> <mi mathvariant="normal">m</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>e</b>) total power coefficient, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">p</mi> <mi mathvariant="normal">t</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>The plots of vorticity for Case 4 at various leading pitch angles and time steps: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mo>ψ</mo> </mrow> <mrow> <mi mathvariant="normal">o</mi> </mrow> </msub> </mrow> </semantics></math> = 45°; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mo>ψ</mo> </mrow> <mrow> <mi mathvariant="normal">o</mi> </mrow> </msub> </mrow> </semantics></math> = 50°; and (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mo>ψ</mo> </mrow> <mrow> <mi mathvariant="normal">o</mi> </mrow> </msub> </mrow> </semantics></math> = 55°.</p>
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<p>Pressure coefficient for Case 4 at various leading flap pitch angles and time steps: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mo>ψ</mo> </mrow> <mrow> <mi mathvariant="normal">o</mi> </mrow> </msub> </mrow> </semantics></math> = 45°; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mo>ψ</mo> </mrow> <mrow> <mi mathvariant="normal">o</mi> </mrow> </msub> </mrow> </semantics></math> = 50°; and (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mo>ψ</mo> </mrow> <mrow> <mi mathvariant="normal">o</mi> </mrow> </msub> </mrow> </semantics></math> = 55°.</p>
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<p>Average total power coefficient (<math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">p</mi> <mi mathvariant="normal">t</mi> </mrow> </msub> </mrow> </semantics></math>) for a wing with two flaps using a hybrid pitching motion: (<b>a</b>) LF25%, W55%, TF20%; (<b>b</b>) LF30%, W50%, TF20%; (<b>c</b>) LF30%, W55%, TF15%; and (<b>d</b>) LF35%, W45%, TF20% for Case 4 at wing pitch angle = 85° and various flap pitch angles.</p>
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20 pages, 18170 KiB  
Article
Accurate Suspension Force Modeling and Its Control System Design Based on the Consideration of Degree-of-Freedom Interaction
by Weiyu Zhang and Aojie Xu
Actuators 2025, 14(2), 61; https://doi.org/10.3390/act14020061 - 26 Jan 2025
Viewed by 202
Abstract
In this study, an accurate suspension force modeling method for the magnetic bearings of flywheel batteries considering degree-of-freedom (DOF) interactions and their control system is proposed to solve the problem that the traditional flywheel battery suspension force model does not consider DOF interactions, [...] Read more.
In this study, an accurate suspension force modeling method for the magnetic bearings of flywheel batteries considering degree-of-freedom (DOF) interactions and their control system is proposed to solve the problem that the traditional flywheel battery suspension force model does not consider DOF interactions, which makes the control system control effect poor. Firstly, according to the structural characteristics of the flywheel battery used, a suspension force model is established for the radial and axial magnetic bearings, which are most seriously interfered with by the torsional degrees of freedom of the flywheel battery. Next, by proposing DOF interaction factors, the complex changes due to DOF interactions are cleverly summarized into several interaction factors applied to the fundamental model to achieve accurate suspension force modeling considering DOF interactions. To better adapt the established accurate model and ensure precise control of the flywheel battery system under various working conditions, the firefly algorithm is employed to optimize the BP neural network (FA-BPNN). This optimization regulates the control system’s parameters, enabling the achievement of optimal control parameters in different scenarios and enhancing control efficiency. Compared to the flywheel battery controlled using the fundamental model, the radial and axial displacements are reduced by more than 30 percent and 20 percent, respectively, in the uphill condition using the accurate model with FA-BPNN. Full article
(This article belongs to the Special Issue Actuators in Magnetic Levitation Technology and Vibration Control)
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<p>The overall structure of the vehicle-mounted flywheel battery and its magnetic circuit.</p>
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<p>Variation in suspension force under torsion by finite element simulation: (<b>a</b>) Axial magnetic bearing. (<b>b</b>) Radial magnetic bearing.</p>
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<p>Comparison of finite element simulation, linear suspension force calculation, and nonlinear suspension force calculation results: (<b>a</b>) <span class="html-italic">x</span>-direction and (<b>b</b>) <span class="html-italic">y</span>-direction.</p>
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<p>Changes in the three-phase air gaps and magnetic flux density during torsion by finite element simulation: (<b>a</b>) Air gaps. (<b>b</b>) Magnetic flux density in air gap (B-phase).</p>
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<p>Magnetic flux density at different torsion angles by finite element simulation.</p>
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<p>Equivalent magnetic flux considering torsion correction angle under different torsion angles.</p>
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<p>Comparison of current magnetic flux density stiffness in torsional and non-torsional cases by finite element simulation.</p>
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<p>Comparison between accurate suspension model and finite element calculation results: (<b>a</b>) <span class="html-italic">x</span>-direction and (<b>b</b>) <span class="html-italic">y</span>-direction.</p>
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<p>Axial air gap magnetic flux density obtained by finite element simulation: (<b>a</b>) Axial air gap. (<b>b</b>) Axial torsion shared air gap.</p>
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<p>(<b>a</b>) Comparison between accurate suspension force model and finite element calculation results. (<b>b</b>) Axial current magnetic flux density stiffness.</p>
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<p>FA-BP neural network control parameter adjustment model.</p>
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<p>FA-BPNN algorithm flow chart.</p>
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<p>Comparison of experimental and model predictions: (<b>a</b>) FA-BPNN. (<b>b</b>) GA-BPNN. (<b>c</b>) BPNN.</p>
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<p>Comparison of training errors among different algorithms.</p>
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<p>(<b>a</b>) Experimental platform for moving vehicle driving conditions. (<b>b</b>) Schematic diagram of the uphill experiment.</p>
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<p>Diagram of magnetic suspension control system.</p>
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<p>Comparison of accurate models and experiments: (<b>a</b>) radial <span class="html-italic">x</span>-direction force–current stiffness comparison. (<b>b</b>) Axial <span class="html-italic">z</span>-direction stiffness comparison. (<b>c</b>) Radial force–displacement stiffness comparison.</p>
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<p>Waveforms of uphill experiments with <span class="html-italic">x</span>-direction offset: (<b>a</b>) Using the fundamental model without control parameters adjusted in the uphill 5 deg case. (<b>b</b>) Using the accurate model with FA-BPNN in the uphill 5 deg case. (<b>c</b>) Using the fundamental model without control parameters adjusted in the uphill 10 deg case. (<b>d</b>) Using the accurate model with FA-BPNN in the uphill 10 deg case.</p>
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<p>Waveforms of uphill experiments with <span class="html-italic">z</span>-direction offset: (<b>a</b>) Using the fundamental model without control parameters adjusted in the uphill 5 deg case. (<b>b</b>) Using the accurate model with FA-BPNN in the uphill 5 deg case. (<b>c</b>) Using the fundamental model without control parameters adjusted in the uphill 10 deg case. (<b>d</b>) Using the accurate model with FA-BPNN in the uphill 10 deg case.</p>
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15 pages, 2824 KiB  
Article
The Technical Development of a Prototype Lower-Limb Therapy Device for Bed-Resting Users
by Juan Fang, Adrien Cerrito, Simón Gamero Schertenleib, Patrick von Raumer and Kai-Uwe Schmitt
Actuators 2025, 14(2), 60; https://doi.org/10.3390/act14020060 - 26 Jan 2025
Viewed by 216
Abstract
It is generally recommended that bed-resting patients be mobilised early to promote recovery. The aim of this work was to develop and evaluate the usability of a prototype in-bed lower-limb therapy device that offers various training patterns for the feet and legs, featuring [...] Read more.
It is generally recommended that bed-resting patients be mobilised early to promote recovery. The aim of this work was to develop and evaluate the usability of a prototype in-bed lower-limb therapy device that offers various training patterns for the feet and legs, featuring an intuitive user interface and interactive exergames. Based on clinical interviews, the user requirements for the device were determined. The therapy device consisted of two compact foot platforms with integrated electric motors and force sensors. Movement control strategies and a user interface with computer games were developed. Through a touch screen, the target force and position trajectories were defined. Using automatic position and force control algorithms, the device produced leg flexion/extension with synchronised ankle plantarflexion/dorsiflexion as well as leg pressing with adjustable resistive loading. An evaluation test on 12 able-bodied participants showed that the device produced passive (mean position control errors: 8.91 mm linearly and 1.62° in the ankle joints) and active leg training (force control error: 2.52 N). The computer games were proven to be interesting, engaging, and responsive to the training movement. It was demonstrated that the device was technically usable in terms of mechatronics, movement control, user interface, and computer games. The advancements in well-controlled movement, multi-modal training patterns, convenient operation, and intuitive feedback enable the compact therapy device to be a potential system for bed-resting users to improve physical activity and cognitive functionality. Full article
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<p>CAD of the lower-limb therapy device. The system housing, the foot plates, and the cases for the foot platforms were removed so as to show the drives and mechanical components. (1) Motor for linear movement, (2) motor for ankle dorsiflexion/plantarflexion, and (3) force sensor.</p>
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<p>The prototype of the lower-limb therapy device on a medical bed (<b>a</b>) and with a test person (<b>b</b>): (1) touch screen, (2) emergency stop, (3) foot plate, and (4) force sensor.</p>
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<p>Control algorithms. (<b>a</b>) Position control. (<b>b</b>) Force control.</p>
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<p>System programming architecture. The red dotted line means communication between the Microcontroller and the Motor controller. The green dotted line indicates data export and transport using a USB-Key.</p>
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<p>The pages for the user interface: (<b>a</b>) Testing, (<b>b</b>) Computer Game, and (<b>c</b>) Data.</p>
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<p>An example of the computer game’s sinusoidal curve: (<b>a</b>) game setup, and (<b>b</b>) computer game shown on the touch screen. (1) Moving point and (2) coin.</p>
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<p>Passive position control of the right leg of a representative participant (P5). (<b>a</b>,<b>b</b>) the position of the foot platform and the motor velocity to produce the linear movement. (<b>c</b>,<b>d</b>) the position of the ankle joint and the motor velocity to produce dorsiflexion/plantarflexion.</p>
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<p>Force control of the active load on the right leg of the representative participant (P5). (<b>a</b>–<b>c</b>) are the force, motor current and the linear movement during the active training.</p>
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23 pages, 5393 KiB  
Article
A SAC-Bi-RRT Two-Layer Real-Time Motion Planning Approach for Robot Assembly Tasks in Unstructured Environments
by Qinglei Zhang, Siyao Hu, Jianguo Duan, Jiyun Qin and Ying Zhou
Actuators 2025, 14(2), 59; https://doi.org/10.3390/act14020059 - 26 Jan 2025
Viewed by 231
Abstract
Due to the uncertainty and complexity of the assembly process, the trajectory planning of a robot needs to consider the real-time obstacle avoidance problem when it completes the assembly in the unstructured workspace. To realize the safe assembly of assembly robots in dynamic [...] Read more.
Due to the uncertainty and complexity of the assembly process, the trajectory planning of a robot needs to consider the real-time obstacle avoidance problem when it completes the assembly in the unstructured workspace. To realize the safe assembly of assembly robots in dynamic and complex environments, a dynamic obstacle avoidance trajectory planning method for robots combining traditional planning algorithms and deep reinforcement learning algorithms is proposed to improve the robot’s agent and obstacle avoidance ability in dynamic and complex environments. The Bidirectional Rapidly-exploring Random Tree (Bi-RRT) method is utilized as a global planner to plan the global optimal path quickly; considering the real-time nature of the assembly process, the Soft Actor-Critic (SAC) is used as a local obstacle avoider to avoid obstacles more accurately and to find the nearest node generated by the Bi-RRT during the planning process, which is regarded as the goal during the local obstacle avoidance to reduce the model’s complexity. By training and testing in the simulation engine and comparing with SAC, DDPG and DQN algorithms, the method can avoid obstacles in dynamic and complex environments more efficiently, which verifies that the proposed hybrid method can accomplish the high-precision planning task with a high success rate. Full article
(This article belongs to the Section Actuators for Robotics)
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<p>SAC-Bi-RRT motion planning framework (a logical framework for dynamic obstacle avoidance based on the Soft Actor-Critic algorithm with bidirectional fast exploratory random tree joint planning is shown in the figure. The information in the assembly environment is obtained from global and local cameras, and the robotic arm is planned to accomplish the assembly task in the complex environment using a hybrid strategy combining Bi-RRT global path planning and SAC local obstacle avoidance).</p>
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<p>Schematic diagram of Bi-RRT algorithm planning.</p>
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<p>Flowchart of Bi-RRT algorithm.</p>
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<p>Simplified model of AABB envelope.</p>
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<p>Collision detection between robot linkage and obstacles.</p>
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<p>SAC framework diagram.</p>
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<p>Lab bench assembly scene (the left picture shows the working scene of the whole experimental bench; the right picture shows the global camera view, the bottom part is the material table where the workpieces are to be gripped, the center is the two UR robotic arms, and the top part is the rotor carousel to be assembled). The assembly task is to grasp various workpieces on the material table by the robotic arms and assemble them on the rotor carousel above.</p>
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<p>Inspection view during assembly (the left display in the figure shows a localized view of what the RealSense d435i camera can see, and the right display shows the global view of the Kinect V2 camera).</p>
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<p>Simulation of the robotic arm during the training process (the UR5 robotic arm present in the figure takes the position of the workpiece to be gripped or the position to be assembled as the target point, and the various obstacles in the complex environment are assumed to be the obstacles of the square in the figure, so that the robotic arm moves from a random position to the target point position and avoids the dynamic obstacles in the environment in the process).</p>
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<p>Success rate graphs during training (SAC, DDPG, DQN).</p>
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<p>Plot of reward values during training (SAC, DDPG, DQN).</p>
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<p>The whole path planning and dynamic obstacle avoidance process of the robotic arm. ((<b>a</b>) Robot initial position. (<b>b</b>,<b>c</b>) Avoiding dynamic obstacles. (<b>d</b>,<b>e</b>) Movement towards the target. (<b>f</b>) Target location).</p>
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<p>Planned path of the robotic arm in the absence and presence of dynamic obstacles. (<b>a</b>) The RRT algorithm and the SAC-Bi-RRT algorithm are compared. (<b>b</b>) The RRT algorithm and the DDPG-Bi-RRT algorithm are compared. (<b>c</b>) The Bi-RRT algorithm and the SAC algorithm were compared.</p>
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32 pages, 20828 KiB  
Article
Time-Variation Damping Dynamic Modeling and Updating for Cantilever Beams with Double Clearance Based on Experimental Identification
by Yunhe Zhang, Fanjun Meng, Xueguang Li, Wei Song, Dashun Zhang and Faping Zhang
Actuators 2025, 14(2), 58; https://doi.org/10.3390/act14020058 - 26 Jan 2025
Viewed by 218
Abstract
The accuracy of a space manipulator’s end trajectory and stability is significantly affected by joint clearance. Aiming to improve the prediction accuracy of vibration caused by clearance, a dynamic clearance modeling method is developed based on parameter identification in this study. First, a [...] Read more.
The accuracy of a space manipulator’s end trajectory and stability is significantly affected by joint clearance. Aiming to improve the prediction accuracy of vibration caused by clearance, a dynamic clearance modeling method is developed based on parameter identification in this study. First, a dynamic model framework for manipulator arms is established based on the Hamilton principle and hypothetical mode method with time-variation damping. Then, a multi-resolution identification is performed for identifying the instantaneous frequency and damping ratio to estimate stiffness and damping by the sensors. The quantum genetic algorithm (QGA) is used to optimize the scale factor, which determines the identification accuracy and calculation efficiency. Finally, a case study is conducted to verify the presented model. In comparison with the initial dynamic model based on constant damping, the modal assurance criterion (MAC) of the proposed improved model based on time-variation damping is improved by 43.97%, the mean relative error (MRE) of the frequency response function (FRF) is reduced by 32.6%, and the root mean square error (RMSE) is reduced by 18.19%. The comparison results indicate the advantages of the proposed model. This modeling method could be used for vibration prediction in control systems for space manipulators to improve control accuracy. Full article
(This article belongs to the Special Issue Power Electronics and Actuators—Second Edition)
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<p>Simplified model.</p>
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<p>Parameter identification.</p>
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<p>Iterative process.</p>
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<p>Identification results and residual curves of the continuous− and step−change damping processes. (<b>a</b>) Identification results of the damping model. (<b>b</b>) Residual curve of the damping model.</p>
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<p>Comparison of the identification accuracy and efficiency. (<b>a</b>) Stacked histogram of multiscale identification. (<b>b</b>) Objective function curve of the QGA.</p>
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<p>Dimensions of contact rings.</p>
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<p>Test model.</p>
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<p>FRF result comparison of the simulation and test models. (<b>a</b>) Clearance position 1. (<b>b</b>) Clearance position 2. (<b>c</b>) Front position. (<b>d</b>) End position.</p>
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<p>Comparison of the FRF correlation coefficients of the two models. In (<b>A</b>) The CSF result comparison. (<b>a</b>) Clearance position 1. (<b>b</b>) Clearance position 2. (<b>c</b>) Front position. (<b>d</b>) End position. In (<b>B</b>) The CSAC result comparison. (<b>a</b>) Clearance position 1. (<b>b</b>) Clearance position 2. (<b>c</b>) Front position. (<b>d</b>) End position.</p>
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<p>Comparison of the FRF correlation coefficients of the two models. In (<b>A</b>) The CSF result comparison. (<b>a</b>) Clearance position 1. (<b>b</b>) Clearance position 2. (<b>c</b>) Front position. (<b>d</b>) End position. In (<b>B</b>) The CSAC result comparison. (<b>a</b>) Clearance position 1. (<b>b</b>) Clearance position 2. (<b>c</b>) Front position. (<b>d</b>) End position.</p>
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<p>FRF results for different clearance values. (<b>a</b>) Clearance 1. (<b>b</b>) Clearance 2. (<b>c</b>) Front position. (<b>d</b>) End position.</p>
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<p>Coincidence degree between the measured and calculated frequencies. (<b>a</b>) First order. (<b>b</b>) Second order. (<b>c</b>) Third order. (<b>d</b>) Fourth order.</p>
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<p>FRF comparison of the simulation and test models (clearance = 0.05 mm).</p>
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<p>FRF comparison of the simulation and test models (clearance = 0.1 mm).</p>
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<p>FRF comparison of the simulation and test models (clearance = 0.5 mm).</p>
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<p>FRF comparison of the simulation and test models (clearance = 1 mm).</p>
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<p>FRF comparison of the simulation and test models (clearance = 1.5 mm).</p>
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<p>FRF comparison of the simulation and test models (clearance = 2 mm).</p>
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<p>CSF result comparison (clearance = 0.05 mm).</p>
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<p>CSAC result comparison (clearance = 0.05 mm).</p>
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<p>SF result comparison (clearance = 0.1 mm).</p>
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<p>CSAC result comparison (clearance = 0.1 mm).</p>
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<p>CSF result comparison (clearance = 0.5 mm).</p>
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<p>CSAC result comparison (clearance = 0.5 mm).</p>
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<p>CSF result comparison (clearance = 1 mm).</p>
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<p>CSAC result comparison (clearance = 1 mm).</p>
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<p>CSF result comparison (clearance = 1.5 mm).</p>
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<p>CSAC result comparison (clearance = 1.5 mm).</p>
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<p>CSF result comparison (clearance = 2 mm).</p>
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<p>CSAC result comparison (clearance = 2 mm).</p>
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<p>Test FRF comparison results at a different clearance.</p>
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19 pages, 478 KiB  
Article
A Robust Cooperative Control Protocol Based on Global Sliding Mode Manifold for Heterogeneous Nonlinear Multi-Agent Systems Under the Switching Topology
by Xiaoyu Zhang, Yining Li, Shuiping Xiong, Xiangbin Liu and Rong Guo
Actuators 2025, 14(2), 57; https://doi.org/10.3390/act14020057 - 25 Jan 2025
Viewed by 280
Abstract
This study addresses the completely distributed consensus control problem for the heterogeneous nonlinear multi-agent system (MAS) with disturbances under switching topology. First, a global sliding mode manifold (GSMM) is designed for the overall MAS dynamic, which maintains stability without oscillations during topology switching [...] Read more.
This study addresses the completely distributed consensus control problem for the heterogeneous nonlinear multi-agent system (MAS) with disturbances under switching topology. First, a global sliding mode manifold (GSMM) is designed for the overall MAS dynamic, which maintains stability without oscillations during topology switching after achieving the sliding mode. Subsequently, a consensus sliding mode control protocol (SMCP) is proposed, adopting the common sliding mode control (SMC) format and ensuring the finite-time reachability of the GSMM under topology switching. Finally, the proposed GSMM and SMCP are applied to the formation control of multiple-wheeled mobile robots (WMRs), and simulation results confirm their feasibility and effectiveness. The proposed SMCP design demonstrates key advantages, including a simple control structure, complete robustness to matched disturbance, and reduced-order dynamics under the sliding mode. Full article
(This article belongs to the Section Control Systems)
21 pages, 861 KiB  
Article
Almost Disturbance Decoupling Control Strategy for a Class of Underactuated Nonlinear Systems with Disturbances
by Renhan Wu, Xiaoping Liu, Tianfei Chen, Lijun Sun and Na Wang
Actuators 2025, 14(2), 56; https://doi.org/10.3390/act14020056 - 25 Jan 2025
Viewed by 253
Abstract
This paper introduces an almost disturbance decoupling approach to address the disturbance problem for a class of underactuated nonlinear systems. First, a residual system is constructed using a virtual controller and partial differential equations. Next, the unknown disturbances are addressed using an almost [...] Read more.
This paper introduces an almost disturbance decoupling approach to address the disturbance problem for a class of underactuated nonlinear systems. First, a residual system is constructed using a virtual controller and partial differential equations. Next, the unknown disturbances are addressed using an almost disturbance decoupling approach, where Young’s inequality is applied to handle the disturbance terms in the residual system. An almost disturbance decoupling controller is designed for the residual system. The locally asymptotic stability of the closed-loop system is rigorously proven using Lyapunov’s theorem. Finally, simulation results on an IWP system with unknown disturbances and experimental results on an overhead crane are presented to validate the effectiveness of the proposed almost disturbance decoupling control method. Full article
(This article belongs to the Section Control Systems)
16 pages, 3334 KiB  
Article
Lead-Free Ceramics in Prestressed Ultrasonic Transducers
by Claus Scheidemann, Peter Bornmann, Walter Littmann and Tobias Hemsel
Actuators 2025, 14(2), 55; https://doi.org/10.3390/act14020055 - 25 Jan 2025
Viewed by 282
Abstract
Today’s ultrasonic transducers find broad application in diverse technology branches and most often cannot be replaced by other actuators. They are typically based on lead-containing piezoelectric ceramics. These should be replaced for environmental and health issues by lead-free alternatives. Multiple material alternatives are [...] Read more.
Today’s ultrasonic transducers find broad application in diverse technology branches and most often cannot be replaced by other actuators. They are typically based on lead-containing piezoelectric ceramics. These should be replaced for environmental and health issues by lead-free alternatives. Multiple material alternatives are already known, but there is a lack of information about their technological readiness level. To fill this gap, a small series of prestressed longitudinally vibrating transducers was set up with a standard PZT material and two lead-free variants within this study. The entire process for building the transducers is documented: characteristics of individual ring ceramics, burn-in results, and free vibration and characteristics under load are shown. The main result is that the investigated lead-free materials are ready to use within ultrasonic bolted Langevin transducers (BLTs) for medium-power applications, when the geometrical setup of the transducer is adopted. Since lead-free ceramics need higher voltages to achieve the same power level, the driving electronics or the mechanical setup must be altered specifically for each material. Lower self-heating of the lead-free materials might be attractive for heat-sensitive processes. Full article
(This article belongs to the Special Issue Piezoelectric Ultrasonic Actuators and Motors)
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<p>BLT design: The backing mass (③), 4 piezoelectric ceramic rings (④), and 5 electrodes (②) are prestressed by a hollow screw (①); the base body (⑤) has an internal thread at its front side to attach a sonotrode (not used within this study).</p>
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<p>Experimental setup: Structure of the actuator in a loaded state (immersed in water) and its electrical control, with a schematic representation of the water circuit and non-contact measurement of the surface temperature of the piezo-elements. Dashed half-circles below the transducer’s front-face symbolize acoustic waves being radiated into water. The dashed lines inside the transducer indicate the central channel for liquid throughput.</p>
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<p>Series of assembled transducers with PZT and lead-free piezoelectric ceramics, plastic mounting bracket, and ATHENA ultrasound generator being used for resonance-controlled operation and measurements.</p>
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<p>Measured frequency responses of the short-circuit input admittance of 50 individual ring ceramics (coloured solid lines) compared to simulation results (dashed black line) for (<b>a</b>) PIC 181, (<b>b</b>) PIC 758, and (<b>c</b>) PIC HQ2. Please refer to the different frequency ranges used in the diagrams for convenience.</p>
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<p>Results of burn-in process (free resonant vibration at ≈1 m/s for ≈6 min): (<b>a</b>) Temperature rise over time, (<b>b</b>) resonance frequency change over temperature rise, (<b>c</b>) voltage related to tip velocity over time, (<b>d</b>) motional current related to tip velocity over temperature rise.</p>
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<p>Small-signal admittance characteristics (free vibration, room temperature).</p>
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<p>Results of tests (resonance-controlled continuous vibration up to 1.5 m/s, heat up over time): (<b>a</b>) Dependency of tip velocity and motional current, (<b>b</b>) mechanical damping factor over tip velocity, (<b>c</b>) ratio of motional current and tip velocity over temperature rise, and (<b>d</b>) mechanical damping factor over temperature rise.</p>
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<p>Results of short-time operation tests; colours stand for different materials (PIC 181: red, PIC 758: blue, PIC HQ2: green): (<b>a</b>) Dependency of tip velocity and motional current for the no-load vibration of the transducer being fixed in the clamping, and (<b>b</b>) active power over motional current at free vibration (dark colours) and under water load (light colours).</p>
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<p>Results of load tests with heating up (immersion of transducer tip into water, controlled vibration at different levels of motional current, continuous drive until steady state temperature): (<b>a</b>) motional current amplitude over time, (<b>b</b>) temperature rise over time, (<b>c</b>) voltage amplitude over time, and (<b>d</b>) active power over motional current amplitude.</p>
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24 pages, 4240 KiB  
Article
Digital Hydraulic Transformer Concepts for Energy-Efficient Motion Control
by Helmut Kogler
Actuators 2025, 14(2), 54; https://doi.org/10.3390/act14020054 - 25 Jan 2025
Viewed by 229
Abstract
Hydraulic linear drive systems with conventional proportional valves result in poor energy efficiency due to resistance control. In systems with multiple actuators connected to one common pressure supply, a load-sensing strategy is often used to reduce these throttling losses. However, like conventional cylinder [...] Read more.
Hydraulic linear drive systems with conventional proportional valves result in poor energy efficiency due to resistance control. In systems with multiple actuators connected to one common pressure supply, a load-sensing strategy is often used to reduce these throttling losses. However, like conventional cylinder actuators, common load-sensing systems are also not able to recuperate the energy, which is actually released when a dead load is lowered. In order to overcome these drawbacks, in this paper, new concepts of a digital hydraulic smart actuator and a load-sensitive pressure supply unit are presented, which are qualified to reduce throttling losses and, furthermore, to harvest energy from the load. According to previous research, the basic concepts used in this contribution promise energy savings in the range of 30% for certain applications, which is one of the main motivations for this study. The operating principles are based on a parallel arrangement of multiple hydraulic switching converters, representing so-called digital hydraulic transformers. Furthermore, the storage module of the presented load-sensitive pressure supply unit is able to boost the hydraulic power in the common pressure rail beyond the maximum power of the primary motor. For exemplary operating cycles of the smart actuator and the pressure supply unit, a significant reduction in the energy consumption could be shown by simulation experiments, which offers a new perspective for energy-efficient motion control. Full article
(This article belongs to the Special Issue Actuation and Control in Digital Fluid Power)
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<p>HERCULES actuator from [<a href="#B15-actuators-14-00054" class="html-bibr">15</a>]. (<b>a</b>) Smart digital hydraulic actuator; (<b>b</b>) scheme with multiple buck converter stages.</p>
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<p>Load-sensitive digital hydraulic application presented in [<a href="#B15-actuators-14-00054" class="html-bibr">15</a>]. (<b>a</b>) Excavator arm with common pressure rail architecture; (<b>b</b>) power consumption for the digging of a trench.</p>
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<p>Digital hydraulic smart actuator (HBC052) with multiple hydraulic buck converters for each pressure chamber.</p>
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<p>Control scheme of HBC052.</p>
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<p>Load-sensitive pressure source using a digital displacement pump (DDP).</p>
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<p>Load-sensitive supply unit with buffer module using an INNAS Hydraulic Transformer.</p>
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<p>Load-sensitive supply unit with buffer module using a digital hydraulic transformer.</p>
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<p>Operating areas of the DHT. (<b>a</b>) Power quadrants; (<b>b</b>) power range.</p>
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<p>Basic motion control of HBC052 in all power quadrants. (<b>a</b>) Tracking control; (<b>b</b>) energy consumption.</p>
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<p>Energy recuperation (<math display="inline"><semantics> <mrow> <msub> <mi>q</mi> <mi>B</mi> </msub> <mo>&lt;</mo> <mn>0</mn> </mrow> </semantics></math>). (<b>a</b>) Power quadrant <math display="inline"><semantics> <msub> <mi mathvariant="script">Q</mi> <mn>2</mn> </msub> </semantics></math> for <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>S</mi> </msub> <mo>&lt;</mo> <msub> <mi>p</mi> <mi>B</mi> </msub> </mrow> </semantics></math>; (<b>b</b>) power quadrant <math display="inline"><semantics> <msub> <mi mathvariant="script">Q</mi> <mn>3</mn> </msub> </semantics></math> for <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>S</mi> </msub> <mo>&gt;</mo> <msub> <mi>p</mi> <mi>B</mi> </msub> </mrow> </semantics></math>.</p>
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<p>Releasing energy from the buffer (<math display="inline"><semantics> <mrow> <msub> <mi>q</mi> <mi>B</mi> </msub> <mo>&gt;</mo> <mn>0</mn> </mrow> </semantics></math>). (<b>a</b>) Power quadrant <math display="inline"><semantics> <msub> <mi mathvariant="script">Q</mi> <mn>1</mn> </msub> </semantics></math> for <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>S</mi> </msub> <mo>&lt;</mo> <msub> <mi>p</mi> <mi>B</mi> </msub> </mrow> </semantics></math>; (<b>b</b>) power quadrant <math display="inline"><semantics> <msub> <mi mathvariant="script">Q</mi> <mn>4</mn> </msub> </semantics></math> for <math display="inline"><semantics> <mrow> <msub> <mi>p</mi> <mi>S</mi> </msub> <mo>&gt;</mo> <msub> <mi>p</mi> <mi>B</mi> </msub> </mrow> </semantics></math>.</p>
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<p>Working cycle with the motor/DDP configuration.</p>
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<p>Supply performance with the buffer module using the DHT.</p>
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<p>Power consumption. (<b>a</b>) DDP without buffer module; (<b>b</b>) DDP with buffer module and DHT.</p>
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<p>Trench-digging cycle with the motor/DDP configuration.</p>
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<p>Power consumption for trench digging with DDP.</p>
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<p>Supply performance for the trench-digging cycle with the buffer module using the DHT.</p>
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<p>Power consumption for the digging of a trench with a DHT.</p>
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16 pages, 5309 KiB  
Article
Optimizing High-Power Performance of [001]-Oriented Pb(Mg1/3Nb2/3)-PbTiO3 Through Combined DC and AC Polarization Above Curie Temperature
by Yuliang Zhu, Xiaobo Wang, Wenchao Xue, Xinran Wen and Chengtao Luo
Actuators 2025, 14(2), 53; https://doi.org/10.3390/act14020053 - 24 Jan 2025
Viewed by 237
Abstract
Pb(Mg1/3Nb2/3)O3-PbTiO3 single crystals (PMN-PT SCs) are widely utilized in high-performance piezoelectric devices due to their exceptional piezoelectric properties. Among the various post-processing techniques for domain engineering in PMN-PT SCs, alternating current polarization (ACP) has become a [...] Read more.
Pb(Mg1/3Nb2/3)O3-PbTiO3 single crystals (PMN-PT SCs) are widely utilized in high-performance piezoelectric devices due to their exceptional piezoelectric properties. Among the various post-processing techniques for domain engineering in PMN-PT SCs, alternating current polarization (ACP) has become a widely adopted method for enhancing piezoelectric performance. This study proposes a new ultrahigh-temperature field-cooling polarization (UFCP) technique, combining direct current polarization (DCP) and ACP with field cooling above the Curie temperature. Dielectric spectra indicate that the UFCP method promotes electric field-induced phase transitions above the Curie point, forming a stable multiphase configuration. The transverse piezoelectric coefficient d31 of UFCP SCs is 1126 pC/N, and the electromechanical coupling factor k31 is 0.559. Compared with traditional DCP, UFCP increases d31 by 68.6%, the mechanical quality factor Qm by 16.7%, and the piezoelectric figure of merit (FOM) by 98.3%. Furthermore, under high-power excitation with a root-mean-square voltage of 15 V, UFCP achieves a 343% increase in power and a 130.5% improvement in the FOM compared with DCP, demonstrating its potential for enhancing high-power performance in practical applications. Full article
(This article belongs to the Special Issue Ultrasonic Transducers for Biomedical Applications)
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<p>Schematic diagrams of (<b>a</b>) ultrahigh-temperature field-cooling polarization (UFCP), (<b>b</b>) ultrahigh-temperature field-cooling direct current polarization (UFC-DCP), (<b>c</b>) field-cooling alternating current polarization (FC-ACP), (<b>d</b>) field-cooling direct current polarization (FC-DCP), (<b>e</b>) room-temperature alternating current polarization (ACP), and (<b>f</b>) room-temperature direct current polarization (DCP) methods.</p>
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<p>(<b>a</b>) Free dielectric constant <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>ε</mi> </mrow> <mrow> <mn>33</mn> </mrow> <mrow> <mi>T</mi> </mrow> </msubsup> <mo>/</mo> <msub> <mrow> <mi>ε</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msub> </mrow> </semantics></math> and dielectric loss at 1 kHz, (<b>b</b>) piezoelectric constant <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>d</mi> </mrow> <mrow> <mn>33</mn> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>d</mi> </mrow> <mrow> <mn>31</mn> </mrow> </msub> <mo>,</mo> </mrow> </semantics></math> (<b>c</b>) electromechanical coupling factor <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mn>31</mn> </mrow> </msub> </mrow> </semantics></math> and elastic compliance <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>s</mi> </mrow> <mrow> <mn>11</mn> </mrow> <mrow> <mi>E</mi> </mrow> </msubsup> </mrow> </semantics></math>, and (<b>d</b>) mechanical quality factor <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>Q</mi> </mrow> <mrow> <mi>m</mi> </mrow> </msub> </mrow> </semantics></math> and piezoelectric figure of merit (FOM) as functions of different polarization methods in small-signal characterization.</p>
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<p>Temperature dependence of <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>ε</mi> </mrow> <mrow> <mn>33</mn> </mrow> <mrow> <mi>T</mi> </mrow> </msubsup> <mo>/</mo> <msub> <mrow> <mi>ε</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msub> </mrow> </semantics></math> at 1 kHz of unpoled, DCP, ACP, and UFCP PMN-PT SCs.</p>
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<p>(<b>a</b>) <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>ε</mi> </mrow> <mrow> <mn>33</mn> </mrow> <mrow> <mi>T</mi> </mrow> </msubsup> <mo>/</mo> <msub> <mrow> <mi>ε</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msub> </mrow> </semantics></math> and dielectric loss at 1 kHz, (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>d</mi> </mrow> <mrow> <mn>33</mn> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>d</mi> </mrow> <mrow> <mn>31</mn> </mrow> </msub> <mo>,</mo> </mrow> </semantics></math> (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mn>31</mn> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>s</mi> </mrow> <mrow> <mn>11</mn> </mrow> <mrow> <mi>E</mi> </mrow> </msubsup> </mrow> </semantics></math>, and (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>Q</mi> </mrow> <mrow> <mi>m</mi> </mrow> </msub> </mrow> </semantics></math> and FOM as functions of ACP PMN-PT SCs poled at different polarization temperatures <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mi>p</mi> </mrow> </msub> </mrow> </semantics></math> in small-signal characterization.</p>
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<p>Impedance spectra as functions of frequency under different root-mean-square (RMS) driving voltages for (<b>a</b>) DCP, (<b>b</b>) ACP, and (<b>c</b>) UFCP PMN-PT SCs.</p>
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<p>(<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>d</mi> </mrow> <mrow> <mn>31</mn> </mrow> </msub> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>Q</mi> </mrow> <mrow> <mi>m</mi> </mrow> </msub> </mrow> </semantics></math>, (<b>c</b>) FOM, (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mn>31</mn> </mrow> </msub> </mrow> </semantics></math>, (<b>e</b>) maximum power at resonant frequency, and (<b>f</b>) maximum vibration velocity at resonant frequency as functions of RMS driving voltage in high-power characterization.</p>
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<p>Impedance spectra as functions of frequency before and after high-power characterization experiments for (<b>a</b>) DCP, (<b>b</b>) ACP, and (<b>c</b>) UFCP PMN-PT SCs in small-signal characterization.</p>
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<p>(<b>a</b>) Voltage, (<b>b</b>) current, (<b>c</b>) power, and (<b>d</b>) vibration velocity of UFCP PMN-PT SC during high-power characterization experiments, with driving RMS voltage set to 15 V as an example.</p>
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<p>Monitoring temperature of PMN-PT SCs during high-power experiments using an infrared thermal camera. (<b>a</b>) Infrared thermography of UFCP PMN-PT SC with driving RMS voltage set to 15 V. (<b>b</b>) Maximum temperature of PMN-PT SCs as a function of RMS driving voltage in high-power characterization.</p>
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16 pages, 4542 KiB  
Article
Energy-Based Adaptive Control for Variable-Rope-Length Double-Pendulum Ship-Borne Cranes: A Disturbance Rejection Stabilization Controller Without Overshoot
by Ken Zhong, Yuzhe Qian, He Chen and Shujie Wu
Actuators 2025, 14(2), 52; https://doi.org/10.3390/act14020052 - 24 Jan 2025
Viewed by 229
Abstract
The operation process of double-pendulum ship-borne cranes with variable rope lengths is frequently complex, with numerous unpredictable circumstances, such as the swing of the load and external environmental interferences, which undoubtedly make the analysis of the swing characteristics of the system and the [...] Read more.
The operation process of double-pendulum ship-borne cranes with variable rope lengths is frequently complex, with numerous unpredictable circumstances, such as the swing of the load and external environmental interferences, which undoubtedly make the analysis of the swing characteristics of the system and the controller design more difficult. On this basis, an active disturbance rejection controller based on an energy coupling method is proposed to inhibit the double-pendulum swing angle. The controller can suppress the swing of the hook and load within 0.5 degrees under the conditions of continuous sea wave disturbances and external disturbances. Firstly, the energy function of the system is constructed by analyzing the dynamic model of the system. Then, an adaptive control method is designed by analyzing the energy function of the system. In addition, an overshoot limit term and an anti-swing term are added to limit the overshoot and swing of underactuated parts of the system. Then, the stability of the closed-loop system is strictly proven by using Lyapunov analysis. Finally, the simulation and experimental results indicate that the proposed controller ensures the accurate positioning of the jib and rope length without overshoot. Additionally, it effectively reduces the double-pendulum swing angle when there is an external interference such as waves, demonstrating strong robustness. Full article
(This article belongs to the Special Issue Modeling and Nonlinear Control for Complex MIMO Mechatronic Systems)
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<p>Schematic diagram of double-pendulum ship-borne crane.</p>
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<p>Flowchart of the overall control system.</p>
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<p>The results of Group 1 and Group 2. (<b>a</b>) The results of Group 1: comparison simulation with PD controller and non-linear controller (blue solid line: the proposed controller; red dotted line: the adaptive controller; green dashed line: the PD controller). (<b>b</b>) The results of Group 2: adding external interference (blue solid line: the proposed controller; red dotted line: the adaptive controller; green dashed line: the PD controller). The interference is added at <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>10</mn> </mrow> </semantics></math> s.</p>
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<p>The results of Group 3 and Group 4. (<b>a</b>) The results of Group 3: increasing the load mass to 1 kg (blue solid line: the proposed controller; red dotted line: the adaptive controller; green dashed line: the PD controller). (<b>b</b>) The results of Group 4: changing the initial and target length of the rope to 0.1 m and 0.4 m, respectively (blue solid line: the proposed controller; red dotted line: the adaptive controller; green dashed line: the PD controller).</p>
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<p>Self-built double-pendulum crane platform.</p>
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<p>The comparison between the experimental results and simulation results (blue solid line: experimental result; red dotted line: simulation result).</p>
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21 pages, 2616 KiB  
Article
Autonomous Tracked Vehicle Trajectory Tracking Control Based on Disturbance Observation and Sliding Mode Control
by Xihao Yan, Shuo Wang, Yuxin He, Aixiang Ma and Sihai Zhao
Actuators 2025, 14(2), 51; https://doi.org/10.3390/act14020051 - 24 Jan 2025
Viewed by 344
Abstract
This paper examines the path-tracking control issue for tracked mobile robots (TMRs) operating in complex terrains, focusing on improving their autonomous operation capabilities. Considering the system’s complex dynamic model, environmental uncertainties, and non-linear characteristics, especially the phenomenon of track slippage, a dynamic model [...] Read more.
This paper examines the path-tracking control issue for tracked mobile robots (TMRs) operating in complex terrains, focusing on improving their autonomous operation capabilities. Considering the system’s complex dynamic model, environmental uncertainties, and non-linear characteristics, especially the phenomenon of track slippage, a dynamic model that incorporates track slippage is proposed. A sliding factor observer is then designed to estimate slippage parameters, ensuring the control system remains stable and accurate despite uncertainties. A hierarchical control architecture is introduced, with the upper-level controller using a kinematic model to generate desired rotational speed commands for the left and right drive wheels. The lower-level controller, operating on a dynamic model, adjusts motor torque to achieve these desired speeds. Utilizing sliding mode control strategies, combined with adaptive laws and nonlinear control methods, the controller effectively addresses the issue of high-frequency chattering arising from the use of signum functions, thereby enhancing the lifespan of actuators and overall system control performance. A comprehensive simulation and experimental setup for real TMR systems is established to validate the proposed control strategy. Results demonstrate that the control scheme effectively achieves trajectory tracking across various unstructured terrains, exhibiting strong robustness and stability. Full article
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<p>Top View of TMR Kinematic Model.</p>
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<p>Top View of TMR Dynamic Model.</p>
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<p>Block Diagram of TMRs Control System.</p>
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<p>Simulation and Experiment Tracking Trajectory of “8” Path. (<b>a</b>) Simulation result, (<b>b</b>) Experiment result.</p>
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<p>Simulation and Experiment Tracking Trajectory of “8” Path. (<b>a</b>) Simulation result, (<b>b</b>) Experiment result.</p>
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<p><span class="html-italic">Y</span>-Direction Trajectory Tracking Performance Curves.</p>
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<p><span class="html-italic">X</span>-Direction Trajectory Tracking Performance Curves.</p>
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<p>Disturbance Observer Estimation Curves. (<b>a</b>) The input and observed value change curve for the left sliding factor, (<b>b</b>) the observed error of the sliding factor.</p>
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<p>TMR Experimental Platform.</p>
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<p>Experimental Result Curves. (<b>a</b>) The change curve of the displacement component in the <span class="html-italic">X</span> direction, (<b>b</b>) the error component in the <span class="html-italic">X</span> direction, (<b>c</b>) the change curve of the displacement component in the <span class="html-italic">Y</span> direction, (<b>d</b>) the error component in the <span class="html-italic">Y</span> direction, (<b>e</b>) the estimated value of the sliding factor on the left side, (<b>f</b>) the speed change curve of the left and right driving wheels.</p>
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23 pages, 9002 KiB  
Article
A Light-Weight Grasping Pose Estimation Method for Mobile Robotic Arms Based on Depthwise Separable Convolution
by Jianguo Duan, Chuyan Ye, Qin Wang and Qinglei Zhang
Actuators 2025, 14(2), 50; https://doi.org/10.3390/act14020050 - 24 Jan 2025
Viewed by 403
Abstract
The robotic arm frequently performs grasping tasks in unstructured environments. However, due to the complex network architecture and constantly changing operational environments, balancing between grasping accuracy and speed poses significant challenges. Unlike fixed robotic arms, mobile robotic arms offer flexibility but suffer from [...] Read more.
The robotic arm frequently performs grasping tasks in unstructured environments. However, due to the complex network architecture and constantly changing operational environments, balancing between grasping accuracy and speed poses significant challenges. Unlike fixed robotic arms, mobile robotic arms offer flexibility but suffer from relatively unstable bases, necessitating improvements in disturbance resistance for grasping tasks. To address these issues, this paper proposes a light-weight grasping pose estimation method called Grasp-DSC, specifically tailored for mobile robotic arms. This method integrates the deep residual shrinkage network and depthwise separable convolution. Attention mechanisms and soft thresholding are employed to improve the arm’s ability to filter out interference, while parallel convolutions enhance computational efficiency. These innovations collectively enhance the grasping decision accuracy and efficiency of mobile robotic arms in complex environments. Grasp-DSC is evaluated using the Cornell Grasp Dataset and Jacquard Grasp Dataset, achieving 96.6% accuracy and a speed of 14.4 ms on the former one. Finally, grasping experiments conducted on the MR2000-UR5 validate the practical applicability of Grasp-DSC in practical scenarios, achieving an average grasping success rate of 96%. Full article
(This article belongs to the Section Actuators for Robotics)
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<p>Network architecture comparison of robotic grasping systems (The left column depicts GG-CNN, the middle column shows GG-CNN 2, an improved variant of GG-CNN, and the right column presents Grasp-DSC, a light-weight grasping pose estimation model proposed in this paper for mobile robotic arms).</p>
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<p>The architecture of Grasp-DSC. (Firstly, each image undergoes normalization and data augmentation preprocessing. Next, the preprocessed images are input into the residual units of the DRSN for deep feature extraction and upsampling. Finally, based on the network outputs, the loss function is computed to determine the grasping pose parameters).</p>
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<p>The architecture of the DRSN (The green dashed box outlines the overall framework, the blue dashed box represents each repeated residual shrinkage module, and the yellow dashed box indicates the thresholding process).</p>
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<p>Two different CNN structures.</p>
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<p>The architecture of DSC. (Each channel is processed individually before linear combination).</p>
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<p>The PW process of DSC. (Altering the depth of feature maps via linear combination).</p>
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<p>Light-weight parallel DSC architecture (Extracting features at different scales using parallel multi-scale convolutional kernels).</p>
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<p>Examples from the Cornell Grasp Dataset.</p>
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<p>Examples from the Jacquard Grasp Dataset.</p>
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<p>Coordinate system for evaluation metrics (Green box represents depth and RGB images captured by the depth camera).</p>
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<p>Training loss variation in different predicted parameters (Curves (<b>a</b>,<b>b</b>) depict training loss curves for grasping angle, (<b>c</b>) for grasping quality, and (<b>d</b>) for grasping width).</p>
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<p>Overall loss trends.</p>
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<p>Comparison of grasping rectangle by different algorithms on the Cornell Grasp Dataset.</p>
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<p>Comparison of grasping success rates of different algorithms on the cornell grasp dataset.</p>
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<p>Comparison of speed of different algorithms on the cornell grasp dataset. (Note: since the speed of GRPN is 189.6, which significantly differs from the other algorithms, it is excluded from the chart).</p>
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<p>MR2000-UR5.</p>
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<p>Experimental process of grasping with MR2000-UR5 mobile robotic arm.</p>
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<p>Comparison of algorithm results from single-object experiment.</p>
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<p>Process of multi-object grasping experiment.</p>
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17 pages, 3706 KiB  
Article
A Study of the Stability of an Industrial Robot Servo System: PID Control Based on a Hybrid Sparrow Optimization Algorithm
by Pengxiang Wang, Tingping Feng, Changlin Song, Junmin Li and Simon X. Yang
Actuators 2025, 14(2), 49; https://doi.org/10.3390/act14020049 - 23 Jan 2025
Viewed by 363
Abstract
Industrial robots can cause servo system instability during operation due to friction between joints and changes in end loads, which results in jittering of the robotic arm. Therefore, this paper proposes a hybrid sparrow search algorithm (HSSA) method for PID parameter optimization. By [...] Read more.
Industrial robots can cause servo system instability during operation due to friction between joints and changes in end loads, which results in jittering of the robotic arm. Therefore, this paper proposes a hybrid sparrow search algorithm (HSSA) method for PID parameter optimization. By studying the optimization characteristics of the genetic algorithm (GA) and sparrow search algorithm (SSA), the method combines the global optimization ability of GA and the local optimization ability of SSA, thus effectively reducing the risk of SSA falling into local optimum and improving the ability of SSA to find global optimization solutions. On the basis of the traditional PID control algorithm, HSSA is used to intelligently optimize the PID parameters so that it can better meet the nonlinear motion of the industrial robot servo system. It is proven through experiments that the HSSA in this paper, compared with GA, SSA, and traditional PID, has a maximum improvement of 73% in the step response time and a maximum improvement of more than 95% in the iterative optimization search speed. The experimental results show that the method has a good suppression effect on the jitter generated by industrial robots in motion, effectively improving the stability of the servo system, so this work greatly improves the stability and safety of industrial robots in operation. Full article
(This article belongs to the Section Actuators for Robotics)
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<p>The PID controller structure.</p>
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<p>A flowchart of the genetic algorithm.</p>
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<p>A flowchart of the HSSA.</p>
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<p>A six-axis industrial robot.</p>
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<p>A simulation of the step system response.</p>
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<p>Iterative convergence curves.</p>
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<p>Movement speed of the robotic arm before the HSSA deployment.</p>
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<p>Movement speed of the robotic arm after the HSSA deployment.</p>
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<p>The robotic arm tracking error before the HSSA deployment.</p>
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<p>The robotic arm tracking error after the HSSA deployment.</p>
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22 pages, 10072 KiB  
Article
Studies on the Thermal Behavior of an Electro-Hydrostatic Servo Actuator
by Liviu Dinca, Jenica-Ileana Corcau, Teodor Lucian Grigorie, Andra-Adelina Cucu and Bogdan Vasilescu
Actuators 2025, 14(2), 48; https://doi.org/10.3390/act14020048 - 23 Jan 2025
Viewed by 323
Abstract
This paper presents a study on the thermal behavior of an electro-hydrostatic servo actuator designed to actuate the ailerons of an airliner. The considered servo actuator was designed using existing commercial off-the-shelf components (electric motor, pump, hydraulic cylinder, valves, hydro-accumulator), and the control [...] Read more.
This paper presents a study on the thermal behavior of an electro-hydrostatic servo actuator designed to actuate the ailerons of an airliner. The considered servo actuator was designed using existing commercial off-the-shelf components (electric motor, pump, hydraulic cylinder, valves, hydro-accumulator), and the control part was tuned using numerical simulations performed in SIMCENTER/AMESIM. This study begins with the functional parameters of the components used in the design and uses numerical simulations to test the thermal behavior of the components. A continuous stress spectrum of the servo actuator is considered, with the servo actuator located in a compartment inside the wing. Different external conditions are also considered, such as situations where component wear occurs and component efficiencies deteriorate, thus producing more heat in the system. Based on the energy losses identified, the average efficiency of the studied servo actuator is also evaluated. Full article
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<p>Schematic of the proposed electro-hydrostatic servo actuator.</p>
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<p>Arrangement of servo actuator components in the wing compartment.</p>
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<p>The considered stress spectrum and the mechanical response to this stress.</p>
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<p>Simulation scheme for the servo system in Simcenter Amesim.</p>
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<p>Simulation results in case 4.1. (<b>a</b>) converter output voltage; (<b>b</b>) converter output current; (<b>c</b>) converter output current (detail); (<b>d</b>) energies produced in the system; (<b>e</b>) energies produced in the system (detail); (<b>f</b>) temperatures of the system components.</p>
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<p>Simulation results in case 4.2. (<b>a</b>) converter output voltage; (<b>b</b>) converter output current; (<b>c</b>) converter output current (detail); (<b>d</b>) energies produced in the system; (<b>e</b>) temperatures of the system components.</p>
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<p>The simulation results for an 1800 s flight at 20 °C as follows: (<b>a</b>) servo in good condition; (<b>b</b>) worn servo.</p>
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<p>The simplified diagram for simulating the thermal behavior of the servo actuator.</p>
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<p>The case with cooling through air recirculation within the compartment. (<b>a</b>) converter temperature; (<b>b</b>) electric motor temperature; (<b>c</b>) hydraulic system temperature; (<b>d</b>) bay temperature; (<b>e</b>) wing skin temperature.</p>
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<p>The case of cooling with air recirculation from the compartment, starting from different initial temperatures. (<b>a</b>) converter temperature; (<b>b</b>) electric motor temperature; (<b>c</b>) hydraulic system temperature; (<b>d</b>) bay temperature.</p>
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<p>External air cooling.</p>
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<p>External air cooling at 40 °C and different flight speeds. (<b>a</b>) converter temperature; (<b>b</b>) electric motor temperature; (<b>c</b>) hydraulic system temperature.</p>
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<p>External air cooling at 60 m/s and different external temperatures. (<b>a</b>) converter temperature; (<b>b</b>) electric motor temperature; (<b>c</b>) hydraulic system temperature.</p>
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<p>External air cooling on a flight with variable speed and external temperature, worn servo actuator. (<b>a</b>) temperatures of the system components; (<b>b</b>) flight speed variation.</p>
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<p>External air cooling on a flight with variable speed and external temperature, servo actuator in a good condition. (<b>a</b>) temperatures of the system components; (<b>b</b>) flight speed variation.</p>
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21 pages, 4819 KiB  
Article
Methane/Air Flame Control in Non-Premixed Bluff Body Burners Using Ring-Type Plasma Actuators
by Fatemeh Bagherighajari, Mohammadmahdi Abdollahzadehsangroudi and José C. Páscoa
Actuators 2025, 14(2), 47; https://doi.org/10.3390/act14020047 - 22 Jan 2025
Viewed by 347
Abstract
Enhancing the combustion efficiency and flame stability in conventional systems is essential for reducing carbon emissions and advancing sustainable energy solutions. In this context, electrohydrodynamic plasma actuators offer a promising active control method for modifying and regulating flame characteristics. This study presents a [...] Read more.
Enhancing the combustion efficiency and flame stability in conventional systems is essential for reducing carbon emissions and advancing sustainable energy solutions. In this context, electrohydrodynamic plasma actuators offer a promising active control method for modifying and regulating flame characteristics. This study presents a numerical investigation into the effects of a ring-type plasma actuator positioned on the co-flow air side of a non-premixed turbulent methane/air combustion system—an approach not previously reported in the literature. The ring-type plasma actuator was designed by placing electrodes along the perimeter of the small diameter wall of the air duct. The impact of the plasma actuator on the reacting flow field within the burner was analyzed, with a focus on its influence on the flow dynamics and flame structure. The results, visualized through velocity and temperature contours, as well as flow streamlines, provide insight into the actuator’s effect on flame behavior. Two operating modes of the plasma actuators were evaluated: co-flow mode, where the aerodynamic effect of the plasma actuators was directed downstream; and counter-flow mode, where the effects were directed upstream. The findings indicate that the co-flow actuation positively reduces the flame height and enhances the flame anchoring at the root, whereas counter-flow actuation slightly weakens the flame root. Numerical simulations further revealed that co-flow actuation marginally increases the energy release by approximately 0.13%, while counter-flow actuation reduces the energy release by around 7.8%. Full article
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<p>Schematic of a single DBD plasma actuator, including the normalized governing equations and boundary conditions for the phenomenological model of the plasma actuator.</p>
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<p>Comparison of the present study’s results for the net thrust generated by the linear plasma actuator with (<b>a</b>) the experimental results of Thomas et al. [<a href="#B32-actuators-14-00047" class="html-bibr">32</a>] and (<b>b</b>) the experimental results of Durscher and Roy [<a href="#B33-actuators-14-00047" class="html-bibr">33</a>].</p>
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<p>Comparison of the plasma-induced velocity profiles from the present study with the experimental results of (<b>a</b>) Thomas et al. [<a href="#B32-actuators-14-00047" class="html-bibr">32</a>] and (<b>b</b>) Durscher and Roy [<a href="#B33-actuators-14-00047" class="html-bibr">33</a>].</p>
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<p>Comparison of the axial and radial velocity profiles with experimental data from (<b>a</b>,<b>b</b>) Dally et al. [<a href="#B20-actuators-14-00047" class="html-bibr">20</a>], (<b>c</b>,<b>d</b>) Tong et al. [<a href="#B36-actuators-14-00047" class="html-bibr">36</a>], and (<b>e</b>) Caetano and da Silva [<a href="#B37-actuators-14-00047" class="html-bibr">37</a>].</p>
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<p>Comparison of the simulation results for the (<b>a</b>,<b>b</b>) temperature profiles and (<b>c</b>) axial and (<b>d</b>) radial velocity profiles for the reacting flow regime with the experimental data of Dally et al. [<a href="#B20-actuators-14-00047" class="html-bibr">20</a>].</p>
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<p>Schematic of the bluff body burner equipped with a ring DBD plasma actuator in the air co-flow stream.</p>
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<p>Computational grid of the burner equipped with a ring DBD plasma actuator.</p>
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<p>Results of grid sensitivity study, based on the variation of the maximum temperatures inside the burner for different grid cell counts.</p>
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<p>Velocity contours with flow streamlines: (<b>a</b>) without the plasma actuator; (<b>b</b>) with the plasma actuator in the co-flow configuration; (<b>c</b>) with the plasma actuator in the counter-flow configuration.</p>
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<p>Temperature contours representing the flame structure: (<b>a</b>) without the plasma actuator; (<b>b</b>) with the plasma actuator in the co-flow configuration; (<b>c</b>) with the plasma actuator in the counter-flow configuration.</p>
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<p>Plot of the differences in temperature between (<b>a</b>) the co-flow and no actuator case and (<b>b</b>) the counter-flow and no actuator case.</p>
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<p>Temperature profiles for the cases without the plasma actuator and with the plasma actuator in the co-flow and counter-flow configurations at (<b>a</b>) x/D<sub>b</sub> = 0.167, (<b>b</b>) x/D<sub>b</sub> = 1.34, and (<b>c</b>) x/D<sub>b</sub> = 4.167 downstream of the bluff body.</p>
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19 pages, 7788 KiB  
Article
Research on Outdoor Navigation of Intelligent Wheelchair Based on a Novel Layered Cost Map
by Jianwei Cui, Siji Yu, Yucheng Shang, Yuxiang Dai and Wenyi Zhang
Actuators 2025, 14(2), 46; https://doi.org/10.3390/act14020046 - 22 Jan 2025
Viewed by 313
Abstract
With the aging of the population and the increase in the number of people with disabilities, intelligent wheelchairs are essential in improving travel autonomy and quality of life. In this paper, we propose an autonomous outdoor navigation framework for intelligent wheelchairs based on [...] Read more.
With the aging of the population and the increase in the number of people with disabilities, intelligent wheelchairs are essential in improving travel autonomy and quality of life. In this paper, we propose an autonomous outdoor navigation framework for intelligent wheelchairs based on hierarchical cost maps to address the challenges of wheelchair navigation in complex and dynamic outdoor environments. First, the framework integrates multi-sensors such as RTK high-precision GPS, IMU, and 3D LIDAR; fuses RTK, IMU, and odometer data to realize high-precision positioning; and performs path planning and obstacle avoidance through dynamic hierarchical cost maps. Secondly, the drivable area layer is integrated into the traditional hierarchical cost map, in which the drivable area detection algorithm utilizes local plane fitting and elevation difference analysis to achieve efficient ground point cloud segmentation and real-time updating, which ensures the real-time safety of navigation. The experiments are validated in real outdoor scenes and simulation environments, and the results show that the speed of drivable region detection is about 30 ms, the positioning accuracy of wheelchair outdoor navigation is less than 10 cm, and the distance of active obstacle avoidance is 1 m. This study provides an effective solution for the autonomous navigation of the intelligent wheelchair in a complex outdoor environment, and it has a high robustness and application potential. Full article
(This article belongs to the Topic Advances in Mobile Robotics Navigation, 2nd Volume)
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<p>Intelligent wheelchair system architecture design. The multimode perception layer integrates a variety of sensor data and is responsible for environment perception and obstacle detection, providing the necessary real-time environmental information for autonomous navigation; the autonomous navigation layer is accountable for path planning and decision-making based on the environment perception information and scheduling the execution of the motion control layer; the communication transmission layer is accountable for realizing data exchange between different components according to the agreed communication protocol; the physical layer is the foundation layer of the whole system, which mainly includes Hardware components of the wheelchair.</p>
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<p>Intelligent wheelchair and sensor installation position.</p>
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<p>Intelligent wheelchair outdoor navigation software architecture, where the red arrows represent the transfer of data, the black arrows represent the role of the function packages, and the blue arrows represent the interaction between the hardware and the data.</p>
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<p>RTK localization architecture diagram.</p>
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<p>Schematic of LiDAR spherical coordinate system. This is a 16-line LiDAR with a horizontal field of view of 360°, a vertical field of view of 30°, a horizontal angular resolution of 1°, and a vertical angular resolution of 2°.</p>
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<p>Schematic of ground point screening based on PCA local ground fitting.</p>
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<p>The red box shows the processing of the point cloud. Firstly, the environmental point cloud data are collected by LiDAR. The point cloud is ground segmented, elevated points are extracted, and a raster of the drivable area is calculated, which is then imported into the hierarchical cost map. The green box shows the updating process of each layer of the hierarchical cost map, and the updating order is from bottom to top. Firstly, the static map is imported to initialize the cost map as shown in (<b>a</b>); the blue grid appears on the static map layer, indicating the static obstacles on the map; then, the LiDAR detects the environmental obstacles, and the obstacle layer is updated as shown in (<b>b</b>). The blue grid appears on the obstacle layer, indicating the static obstacles and the dynamic obstacles detected by the LiDAR. Then, the drivable area is updated based on the imported drivable area raster layer shown in (<b>c</b>). The orange grid indicates the calculated drivable area grid and the blue grid indicates the drivable area boundary and its rear area; finally, the expansion layer is updated according to the detected obstacles by expanding the map, as shown in (<b>d</b>). The gray grid indicates the expansion layer, which enables the wheelchair to stay away from obstacles during path planning; up to this point, the cost map has been completely updated, and the layers are merged into a complete total cost map. (<b>e</b>) The map is updated in real time, and the right blue grid changes position to indicate dynamic obstacle movement.</p>
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<p>Schematic diagram of the target point and wheelchair path planning movement.</p>
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<p>Intelligent wheelchair drivable area detection results.</p>
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<p>Drivable area layered cost map experiment: (<b>a</b>) an accurate picture, (<b>b</b>) the actual point cloud data collected, and (<b>c</b>) cost map, where the white part of the raster has a surrogate value of 0, and the black part represents the non-drivable area which is the layer of the drivable area, the light blue part is the obstacle layer, and the red part is the expansion layer.</p>
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<p>Outdoor path planning experiment. (<b>a</b>) Schematic diagram of the path planning of the Gaode map, and (<b>b</b>) path planning after ROS receives the first target point, the red points are laser points processed by the ground point cloud segmentation algorithm.</p>
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<p>Outdoor path planning experiment. (<b>a</b>) Illustration of obstacles in the actual scene, and (<b>b</b>) cost map and path planning in the presence of obstacles.</p>
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19 pages, 4728 KiB  
Article
Dynamic Envelope Optimization of Articulated Vehicles Based on Multi-Axle Steering Control Strategies
by Zhaocong Sun, Shizhi Yang, Joshua H. Meng, Chi Zhang, Zhousen Cui, Heqian Wang and Wenjun Wang
Actuators 2025, 14(2), 45; https://doi.org/10.3390/act14020045 - 22 Jan 2025
Viewed by 257
Abstract
Steer-by-wire technology, critical for autonomous driving, enables full-wheel steering in articulated vehicles, significantly enhancing maneuverability in complex driving environments. This study investigates dynamic envelope optimization for articulated multi-body vehicles by integrating coordinated multi-axle steering control strategies with higher-order Bezier curve designs. Unlike traditional [...] Read more.
Steer-by-wire technology, critical for autonomous driving, enables full-wheel steering in articulated vehicles, significantly enhancing maneuverability in complex driving environments. This study investigates dynamic envelope optimization for articulated multi-body vehicles by integrating coordinated multi-axle steering control strategies with higher-order Bezier curve designs. Unlike traditional approaches that primarily focus on single-axle steering, this research emphasizes the advantages of multi-axle steering control, which significantly reduces the dynamic envelope and enhances maneuverability. To address the challenges posed by constrained road environments, a comparative analysis of Septimic Bezier curves under various control point configurations was conducted, demonstrating their effectiveness in achieving smoother curvature transitions and steering comfort. The results highlight the pivotal role of reducing curvature peaks and increasing curvature continuity in optimizing vehicle performance. Furthermore, advanced steering control strategies, such as Articulation Angle Reference (AAR) and Dual Ackermann Steering (DAS), were shown to outperform conventional methods by ensuring precise trajectory control and improved stability. This study provides actionable insights for enhancing vehicle handling and safety in complex driving scenarios, offering a framework for future road design and multi-axle steering system development. Full article
(This article belongs to the Special Issue Modeling and Control for Chassis Devices in Electric Vehicles)
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<p>Dynamic envelope calculation based on vehicle trajectories.</p>
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<p>Discrete flowchart of HTR method for articulated vehicles.</p>
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<p>Structure components of articulated vehicles.</p>
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<p>Single-unit vehicle simulation result: (<b>a</b>) steering angle; (<b>b</b>) dynamic envelope; SA represents the results under Single Ackermann methods while DA represents the results under Dual Ackermann methods.</p>
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<p>Articulated vehicle simulation results: (<b>a</b>) steering angle of AAR method; (<b>b</b>) dynamic envelope of AAR method; (<b>c</b>) steering angle of HTR method; (<b>d</b>) dynamic envelope of HTR method.</p>
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<p>Pareto front result of curve design optimization; The X-axis represents the curvature peak, while the Y-axis represents the curvature derivative peak.</p>
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<p>Septimic Bezier curve Case 2: (<b>a</b>) Bezier curve design; (<b>b</b>) curvature and curvature derivative.</p>
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<p>Steering angle of Septimic Bezier curve: (<b>a</b>) Case 2; (<b>b</b>) Case 6.</p>
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<p>Boundary analysis diagram of different multi-axle steering control strategies based on different curves.</p>
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13 pages, 4213 KiB  
Article
Machine Learning Models for Assistance from Soft Robotic Elbow Exoskeleton to Reduce Musculoskeletal Disorders
by Sanjana Suresh, Inderjeet Singh and Muthu B. J. Wijesundara
Actuators 2025, 14(2), 44; https://doi.org/10.3390/act14020044 - 22 Jan 2025
Viewed by 356
Abstract
Musculoskeletal disorders are very common injuries among occupational and healthcare workers. These injuries are preventable in many scenarios using exoskeleton-based assistive technology. Soft robotics initiates an evolution in exoskeleton devices due to their safe human interactions, ergonomic design, and adaptive characteristics. Despite their [...] Read more.
Musculoskeletal disorders are very common injuries among occupational and healthcare workers. These injuries are preventable in many scenarios using exoskeleton-based assistive technology. Soft robotics initiates an evolution in exoskeleton devices due to their safe human interactions, ergonomic design, and adaptive characteristics. Despite their enormous advantages, it is a challenging task to model and control soft robotic devices due to their inherent nonlinearity and hysteresis. Learning-based approaches are becoming more popular to overcome these limitations. This work proposes an approach to estimate the pressure input for a pneumatically actuated soft robotic elbow exoskeleton to assist occupational workers to avoid musculoskeletal disorders. An elbow exoskeleton design made up of modular pneumatic soft actuators is discussed, which helps to flex/extend an elbow joint. Machine learning (ML) approaches are used to develop a relationship between the air pressure, the bending angle of the elbow, and the percentage of the weight of the arm to be assisted by the exoskeleton. The most popular and widely used regression-based ML approaches are applied and compared in terms of accuracy and computation cost. Further, a modified KNN (K-Nearest Neighbor) approach is proposed, which outperforms the accuracy of other approaches. Full article
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<p>Elbow Exoskeleton: (<b>A</b>) soft pneumatic elbow exoskeleton; (<b>B</b>) experimental setup for data collection.</p>
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<p>Pressure vs. angle plot with different weights.</p>
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<p>Plot between mean squared error (MSE) and polynomial degree.</p>
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<p>Plot between mean absolute error (MAE) and number of nearest neighbors (k).</p>
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<p>Plot between mean absolute error (MAE) and tree depth.</p>
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<p>Plot between OOB error and number of trees (<math display="inline"><semantics> <msub> <mi>n</mi> <mi>estimators</mi> </msub> </semantics></math>).</p>
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<p>Plot between OOB error and number of trees (<math display="inline"><semantics> <msub> <mi>n</mi> <mi>estimators</mi> </msub> </semantics></math>).</p>
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<p>Plot between mean absolute error (MAE) and number of neurons for different hidden layers.</p>
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<p>Linear Regression fit with K Nearest Neighbors.</p>
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15 pages, 15889 KiB  
Article
Slewing and Active Vibration Control of a Flexible Single-Link Manipulator
by Dae W. Kim, Moon K. Kwak, Soo-Min Kim and Brian F. Feeny
Actuators 2025, 14(2), 43; https://doi.org/10.3390/act14020043 - 22 Jan 2025
Viewed by 253
Abstract
This study focuses on the slewing and vibration suppression of flexible single-link manipulators. While extensive research has been conducted on such systems, few studies have experimentally validated their theoretical models. To address this gap, an experimental setup is developed, connecting the flexible link [...] Read more.
This study focuses on the slewing and vibration suppression of flexible single-link manipulators. While extensive research has been conducted on such systems, few studies have experimentally validated their theoretical models. To address this gap, an experimental setup is developed, connecting the flexible link to a zero-backlash worm gear and further attaching it to the rotor shaft of the AC servomotor. The worm gear’s characteristics isolate the link’s vibrations from the rotor’s angular motion, enabling independent design of the vibration controller and slewing control. This approach facilitates simultaneous accurate trajectory tracking and vibration suppression. An active vibration control algorithm is implemented based on an accurate dynamic model. This research encompasses dynamic modeling, slewing control, and vibration control for the system. Theoretical predictions are compared with experimental results to validate both the theoretical model and the proposed vibration control algorithm. Full article
(This article belongs to the Special Issue Nonlinear Active Vibration Control)
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Figure 1

Figure 1
<p>A slewing flexible beam with a tip mass.</p>
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<p>Slewing angle trajectory: (<b>a</b>) angle; (<b>b</b>) angular velocity; and (<b>c</b>) angular acceleration.</p>
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<p>Tip acceleration of the slewing beam.</p>
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<p>Numerical slewing angle trajectory without and with active vibration control.</p>
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<p>Numerical tip acceleration response without and with active vibration control.</p>
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<p>Testbed for the slewing experiment.</p>
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<p>Zero-backlash worm gear.</p>
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<p>Simulink block diagram.</p>
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<p>Experimental setup.</p>
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<p>Experimental slewing angle trajectory without and with active vibration control.</p>
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<p>Experimental tip acceleration response without and with active vibration control.</p>
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20 pages, 4298 KiB  
Article
Design and Field Evaluation of an End Effector for Robotic Strawberry Harvesting
by Ezekyel Ochoa and Changki Mo
Actuators 2025, 14(2), 42; https://doi.org/10.3390/act14020042 - 22 Jan 2025
Viewed by 305
Abstract
As the world’s population continues to rise while the agricultural workforce declines, farmers are increasingly challenged to meet the growing food demand. Strawberries grown in the U.S. are especially threatened by such stipulations, as the cost of labor for such a delicate crop [...] Read more.
As the world’s population continues to rise while the agricultural workforce declines, farmers are increasingly challenged to meet the growing food demand. Strawberries grown in the U.S. are especially threatened by such stipulations, as the cost of labor for such a delicate crop remains the bulk of the total production costs. Autonomous systems within the agricultural sector have enormous potential to catalyze the labor and land expansions required to meet the demands of feeding an increasing population, as well as heavily reducing the amount of food waste experienced in open fields. Our team is working to enhance robotic solutions for strawberry production, aiming to improve field processes and better replicate the efficiency of human workers. We propose a modular configuration that includes a Delta X parallel robot and a pneumatically powered end effector designed for precise strawberry harvesting. Our primary focus is on optimizing the design of the end effector and validating its high-speed actuation capabilities. The prototype of the presented end effector achieved high success rates of 94.74% in simulated environments and 100% in strawberry fields at Farias Farms, even when tasked to harvest in the densely covered conditions of the late growing season. Using an off-the-shelf robotic configuration, the system’s workspace has been validated as adequate for harvesting in a typical two-plant-per-row strawberry field, with the hardware itself being evaluated to harvest each strawberry in 2.8–3.8 s. This capability sets the stage for future enhancements, including the integration of the machine vision processes such that the system will identify and pick each strawberry within 5 s. Full article
(This article belongs to the Special Issue Actuators in Robotic Control—3rd Edition)
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<p>Robot architecture of Delta X1 used for strawberry harvesting.</p>
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<p>Optimized 3D-printed end effector design for strawberry harvesting.</p>
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<p>Actuation method of the end effector for the simultaneous cutting, pinching, and holding of strawberry stems: (<b>a</b>) retraction and (<b>b</b>) extension.</p>
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<p>General outline for robotic harvesting procedures.</p>
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<p>Servo motor-driven fourth axis for the end effector.</p>
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<p>The kinematic scheme of a delta robot used for analysis: (<b>a</b>) the coordinates (X, Y, and Z) and the dimensions; and (<b>b</b>) the joint angles (<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>θ</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>θ</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>θ</mi> </mrow> <mrow> <mn>3</mn> </mrow> </msub> </mrow> </semantics></math>) and the end effector position <span class="html-italic">E</span><sub>0</sub> with coordinates x<sub>0</sub>, y<sub>0</sub>, and z<sub>0</sub> [<a href="#B30-actuators-14-00042" class="html-bibr">30</a>].</p>
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<p>Comparison of simulated (green) and actual (blue) workspace for Delta X1 in MATLAB: (<b>a</b>) XY planar view; (<b>b</b>) YZ planar view; (<b>c</b>) XZ planar view; and (<b>d</b>) 3D view.</p>
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<p>Simulated validation of the manually determined Delta X1 workspace compared to a typical two-plant-per-row strawberry field: (<b>a</b>) XZ planar view; (<b>b</b>) XY planar view; and (<b>c</b>) 3D view.</p>
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<p>(<b>a</b>) Simulated validation of end effector hook in Blender, with the original configuration, and (<b>b</b>) magnified view of the stem and the end effector hook.</p>
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<p>Simulated validation of end effector in Blender with the optimized configuration: (<b>a</b>) hook perpendicular to stem extrusion at 0 degrees; (<b>b</b>) hook parallel to stem extrusion at +90 degrees; and (<b>c</b>) hook positioned parallel to the stem at +45 degree angle.</p>
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<p>Field testing validation of the end effector in its optimal configuration.</p>
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<p>(<b>a</b>) Simulated visualization of worst-case scenario harvesting using a delta robot in MATLAB and (<b>b</b>) Simulink plot of moving platform velocities during motion.</p>
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