U-Model-Based adaptive sliding mode control using a deep deterministic policy gradient

Lei, Changyi; Zhu, Quanmin

Abstract

This paper presents a U-model-based adaptive sliding mode control (SMC) using a deep deterministic policy gradient (DDPG) for uncertain nonlinear systems. The configuration of the proposed methodology consisted of a U-model framework and an SMC with a variable boundary layer. The U-model framework forms the outer feedback loop that adjusts the overall performance of the nonlinear system, while SMC serves as a robust dynamic inverter that cancels the nonlinearity of the original plant. Besides, to alleviate the chattering problem while maintaining the intrinsic advantages of SMC, a DDPG network is designed to adaptively tune the boundary and switching gain. From the control perspective, this controller combines the interpretability of the U-model and the robustness of the SMC. From the deep reinforcement learning (DRL) point of view, the DDPG calculates nearly optimal parameters for SMC based on current states and maximizes its favourable features while minimizing the unfavourable ones. The simulation results of the single-pendulum system are compared with those of a U-model-based SMC optimized by the particle swarm optimization (PSO) algorithm. The comparison, as well as model visualization, demonstrates the superiority of the proposed methodology.

• Journal Article Type: Article
• Acceptance Date: Sep 21, 2022
• Online Publication Date: Oct 7, 2022
• Publication Date: Oct 7, 2022
• Deposit Date: Oct 25, 2022
• Journal: Mathematical Problems in Engineering
• Print ISSN: 1024-123X
• Electronic ISSN: 1563-5147
• Publisher: Hindawi
• Peer Reviewed: Peer Reviewed
• Volume: 2022
• Article Number: 8980664
• Pages: 1-14
• Series Title: From Complexity to Simplicity in U-model Enhanced Control System Design 2021
• DOI: https://doi.org/10.1155/2022/8980664
• Keywords: General Engineering, General Mathematics
• Public URL: https://uwe-repository.worktribe.com/output/10104102
• Publisher URL: https://www.hindawi.com/journals/mpe/2022/8980664/
• Related Public URLs: https://www.hindawi.com/journals/mpe/si/962834/
• Additional Information: The simulation data are generated using Python, specifically sine wave function and random values. The source code can be accessed through https://github.com/AndyRay1998/RL-SMC-U.