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Robust tracking control for magnetic wheeled mobile robots using adaptive dynamic programming.

Hongwei Fang1, Yuqi Zhu1, Songyi Dian1

  • 1College of Electrical Engineering, Sichuan University, Chengdu, 610065, China.

ISA Transactions
|November 10, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces an adaptive dynamic programming (ADP) method for robust tracking control of magnetic wheeled mobile robots (MWMR). The approach ensures precise control despite unknown system uncertainties, outperforming traditional methods.

Keywords:
Adaptive dynamic programming (ADP)Magnetic wheeled mobile robot (MWMR)Optimal tracking controlRobust tracking control

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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Artificial Intelligence

Background:

  • Magnetic Wheeled Mobile Robots (MWMR) present complex tracking control challenges due to inherent uncertainties.
  • Existing control methods often struggle with time-varying unknown disturbances in continuous-time systems.

Purpose of the Study:

  • To develop an online robust tracking control scheme for MWMR using Adaptive Dynamic Programming (ADP).
  • To address the challenge of optimal tracking control in the presence of time-varying unknown uncertainties.

Main Methods:

  • An Adaptive Dynamic Programming (ADP) approach with a single critic Neural Network (NN)-based actor-critic structure was employed.
  • Controller architecture was simplified using this structure.
  • Bellman error minimization via gradient descent and least-squares updating laws optimized critic NN weights online.

Main Results:

  • The proposed ADP scheme achieved precise approximation of the optimal cost function and control signal.
  • Lyapunov stability theorem confirmed the convergence of critic NN weights and closed-loop system stability.
  • Simulations demonstrated superior performance compared to robust PD and adaptive control methods.

Conclusions:

  • The developed online robust tracking control scheme effectively manages MWMR control problems with uncertainties.
  • The ADP-based method offers a precise and stable solution for complex robotic tracking tasks.