Regular Papers

International Journal of Control, Automation and Systems 2021; 19(2): 1139-1150

Published online December 6, 2020

https://doi.org/10.1007/s12555-019-0912-9

© The International Journal of Control, Automation, and Systems

Adaptive Reinforcement Learning Strategy with Sliding Mode Control for Unknown and Disturbed Wheeled Inverted Pendulum

Phuong Nam Dao* and Yen-Chen Liu

Hanoi University of Science and University

Abstract

This paper develops a novel adaptive integral sliding-mode control (SMC) technique to improve the tracking performance of a wheeled inverted pendulum (WIP) system, which belongs to a class of continuous time systems with input disturbance and/or unknown parameters. The proposed algorithm is established based on an integrating between the advantage of online adaptive reinforcement learning control and the high robustness of integral sliding-mode control (SMC) law. The main objective is to find a general structure of integral sliding mode control law that can guarantee the system state reaching a sliding surface in finite time. An adaptive/approximate optimal control based on the approximate/adaptive dynamic programming (ADP) is responsible for the asymptotic stability of the closed loop system. Furthermore, the convergence possibility of proposed output feedback optimal control was determined without the convergence of additional state observer. Finally, the theoretical analysis and simulation results validate the performance of the proposed control structure.

Keywords Adaptive reinforcement learning control, approximate/adaptive dynamic programming (ADP), integral sliding mode control (SMC), output feedback control, wheeled inverted pendulum (WIP).

Article

Regular Papers

International Journal of Control, Automation and Systems 2021; 19(2): 1139-1150

Published online February 1, 2021 https://doi.org/10.1007/s12555-019-0912-9

Copyright © The International Journal of Control, Automation, and Systems.

Adaptive Reinforcement Learning Strategy with Sliding Mode Control for Unknown and Disturbed Wheeled Inverted Pendulum

Phuong Nam Dao* and Yen-Chen Liu

Hanoi University of Science and University

Abstract

This paper develops a novel adaptive integral sliding-mode control (SMC) technique to improve the tracking performance of a wheeled inverted pendulum (WIP) system, which belongs to a class of continuous time systems with input disturbance and/or unknown parameters. The proposed algorithm is established based on an integrating between the advantage of online adaptive reinforcement learning control and the high robustness of integral sliding-mode control (SMC) law. The main objective is to find a general structure of integral sliding mode control law that can guarantee the system state reaching a sliding surface in finite time. An adaptive/approximate optimal control based on the approximate/adaptive dynamic programming (ADP) is responsible for the asymptotic stability of the closed loop system. Furthermore, the convergence possibility of proposed output feedback optimal control was determined without the convergence of additional state observer. Finally, the theoretical analysis and simulation results validate the performance of the proposed control structure.

Keywords: Adaptive reinforcement learning control, approximate/adaptive dynamic programming (ADP), integral sliding mode control (SMC), output feedback control, wheeled inverted pendulum (WIP).

IJCAS
February 2024

Vol. 22, No. 2, pp. 347~729

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