Tsai et al., 2007 - Google Patents
Robust tracking control for a wheeled mobile manipulator with dual arms using hybrid sliding‐mode neural networkTsai et al., 2007
View PDF- Document ID
- 1576070015668107260
- Author
- Tsai C
- Cheng M
- Lin S
- Publication year
- Publication venue
- Asian Journal of Control
External Links
Snippet
In this paper, a robust tracking controller is proposed for the trajectory tracking problem of a dual‐arm wheeled mobile manipulator subject to some modeling uncertainties and external disturbances. Based on backstepping techniques, the design procedure is divided into two …
- 230000001537 neural 0 title abstract description 16
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
- G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/39—Robotics, robotics to robotics hand
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B17/00—Systems involving the use of models or simulators of said systems
- G05B17/02—Systems involving the use of models or simulators of said systems electric
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B11/00—Automatic controllers
- G05B11/01—Automatic controllers electric
- G05B11/32—Automatic controllers electric with inputs from more than one sensing element; with outputs to more than one correcting element
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Xu et al. | Trajectory tracking control of omnidirectional wheeled mobile manipulators: robust neural network-based sliding mode approach | |
Yang et al. | Neural network-based motion control of an underactuated wheeled inverted pendulum model | |
Jung | Improvement of tracking control of a sliding mode controller for robot manipulators by a neural network | |
Yue et al. | An efficient model predictive control for trajectory tracking of wheeled inverted pendulum vehicles with various physical constraints | |
Prakash et al. | Dual-loop optimal control of a robot manipulator and its application in warehouse automation | |
Wu et al. | Vision-based neural predictive tracking control for multi-manipulator systems with parametric uncertainty | |
Obregón-Flores et al. | Predefined-time robust hierarchical inverse dynamics on torque-controlled redundant manipulators | |
Fang et al. | Robust tracking control for magnetic wheeled mobile robots using adaptive dynamic programming | |
Tsai et al. | Robust tracking control for a wheeled mobile manipulator with dual arms using hybrid sliding‐mode neural network | |
Pham et al. | Balancing and tracking control of ballbot mobile robots using a novel synchronization controller along with online system identification | |
Martins et al. | Motion control and velocity-based dynamic compensation for mobile robots | |
Moudoud et al. | Robust adaptive trajectory tracking control based on sliding mode of electrical wheeled mobile robot | |
Jun-Pei et al. | Neural network control of space manipulator based on dynamic model and disturbance observer | |
Lin et al. | Hybrid adaptive fuzzy controllers with application to robotic systems | |
Tsai et al. | Dynamic modeling and tracking control of a nonholonomic wheeled mobile manipulator with dual arms | |
Tan et al. | Controlling robot manipulators using gradient-based recursive neural networks | |
Alavandar et al. | New hybrid adaptive neuro-fuzzy algorithms for manipulator control with uncertainties–Comparative study | |
Tsai et al. | Adaptive RFWCMAC cooperative formation control for multiple ballbots incorporated with coupling dynamics | |
Korayem et al. | Wheel slippage compensation in mobile manipulators through combined kinematic, dynamic, and sliding mode control | |
Seçil et al. | Robust position/force control of nonholonomic mobile manipulator forconstrained motion on surface in task space | |
Prado et al. | Intelligent Swing-Up and Robust Stabilization via Tube-based Nonlinear Model Predictive Control for A Rotational Inverted-Pendulum System: Intelligent Swing-Up and Robust Stabilization via Tube-based Nonlinear Model Predictive Control for A Rotational Inverted-Pendulum System | |
Panwar et al. | Design of optimal hybrid position/force controller for a robot manipulator using neural networks | |
Cheng et al. | Robust backstepping tracking control using hybrid sliding-mode neural network for a nonholonomic mobile manipulator with dual arms | |
Akbarimajd et al. | NARMA-L2 controller for 2-DoF underactuated planar manipulator | |
Xu et al. | Trajectory tracking control of omnidirecitonal wheeled mobile manipulators: Robust neural network based sliding mode approach |