Khan et al., 2024 - Google Patents
Stabilization of wheeled mobile robot by social spider algorithm based PID controllerKhan et al., 2024
- Document ID
- 3653908476017221838
- Author
- Khan H
- Khatoon S
- Gaur P
- Publication year
- Publication venue
- International Journal of Information Technology
External Links
Snippet
Mobile robot is an automatic vehicle and it can move automatically from one place to another with a motor built up in its wheels for mobility purpose controlled using a controller. Robot speed may vary by changing the direction of vehicle and to avoid this, social spider …
- 238000004422 calculation algorithm 0 title abstract description 35
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
- G05D1/0291—Fleet control
- G05D1/0295—Fleet control by at least one leading vehicle of the fleet
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
-
- 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
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
-
- 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
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/0011—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement
- G05D1/0044—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement by providing the operator with a computer generated representation of the environment of the vehicle, e.g. virtual reality, maps
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D2201/00—Application
- G05D2201/02—Control of position of land vehicles
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Gheisarnejad et al. | An intelligent non-integer PID controller-based deep reinforcement learning: Implementation and experimental results | |
Hwang et al. | Path tracking of an autonomous ground vehicle with different payloads by hierarchical improved fuzzy dynamic sliding-mode control | |
Nascimento et al. | Nonholonomic mobile robots' trajectory tracking model predictive control: a survey | |
Al-Mayyahi et al. | Path tracking of autonomous ground vehicle based on fractional order PID controller optimized by PSO | |
Peng et al. | Coordinated motion control for a wheel-leg robot with speed consensus strategy | |
Keymasi Khalaji et al. | Dynamic modeling and tracking control of a car with n trailers | |
Alouache et al. | Fuzzy logic PD controller for trajectory tracking of an autonomous differential drive mobile robot (ie Quanser Qbot) | |
Gul et al. | A review of controller approach for autonomous guided vehicle system | |
Eski et al. | Control of unmanned agricultural vehicles using neural network-based control system | |
Khan et al. | Stabilization of wheeled mobile robot by social spider algorithm based PID controller | |
Zuo et al. | Adaptive robust control strategy for rhombus-type lunar exploration wheeled mobile robot using wavelet transform and probabilistic neural network | |
Hwang et al. | Software/hardware-based hierarchical finite-time sliding-mode control with input saturation for an omnidirectional autonomous mobile robot | |
Bhourji et al. | Reinforcement learning ddpg–ppo agent-based control system for rotary inverted pendulum | |
Martins et al. | Motion control and velocity-based dynamic compensation for mobile robots | |
Korayem et al. | Regulation of cost function weighting matrices in control of WMR using MLP neural networks | |
Gao et al. | Reinforcement learning based online parameter adaptation for model predictive tracking control under slippery condition | |
Abdolahi et al. | A New Self‐Tuning Nonlinear Model Predictive Controller for Autonomous Vehicles | |
Korayem et al. | Adaptive robust control with slipping parameters estimation based on intelligent learning for wheeled mobile robot | |
Al‐Araji | Design of a cognitive neural predictive controller for mobile robot | |
Huang et al. | Optimal fuzzy controller design using an evolutionary strategy-based particle swarm optimization for redundant wheeled robots | |
Panwar et al. | Motor velocity based multi-objective genetic algorithm controlled navigation method for two-wheeled pioneer P3-DX robot in V-REP scenario | |
Korayem et al. | Wheel slippage compensation in mobile manipulators through combined kinematic, dynamic, and sliding mode control | |
Sun et al. | Development and Implementation of a wheeled inverted pendulum vehicle using adaptive neural control with extreme learning machines | |
Tao et al. | Path following of autonomous vehicles with an optimized brain emotional learning–based intelligent controller | |
Panwar et al. | Generalised regression neural network (GRNN) architecture-based motion planning and control of an e-puck robot in V-Rep software platform |