Reinforcement-learning-based Adaptive Tracking Control for a Space Continuum Robot Based on Reinforcement Learning

Authors

Da Jiang, 1.Dalian University of Technology, Dalian 116024, China;Follow
Zhiqin Cai, 1.Dalian University of Technology, Dalian 116024, China;Follow
Zhongzhen Liu, 1.Dalian University of Technology, Dalian 116024, China;
Haijun Peng, 1.Dalian University of Technology, Dalian 116024, China;2.State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian 116024, China;
Zhigang Wu, 2.State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian 116024, China;

Abstract

Abstract: Aiming at the tracking control for three-arm space continuum robot in space active debris removal manipulation, an adaptive sliding mode control algorithm based on deep reinforcement learning is proposed. Through BP network, a data-driven dynamic model is developed as the predictive model to guide the reinforcement learning to adjust the sliding mode controller's parameters online, and finally realize a real-time tracking control. Simulation results show that the proposed data-driven predictive model can accurately predict the robot's dynamic characteristics with the relative error within ±1% to random trajectories. Compared with the fixed-parameter sliding mode controller, the proposed adaptive controller has a lower overshoot and shorter settling time and can achieve a better tracking performance.

Recommended Citation

Jiang, Da; Cai, Zhiqin; Liu, Zhongzhen; Peng, Haijun; and Wu, Zhigang (2022) "Reinforcement-learning-based Adaptive Tracking Control for a Space Continuum Robot Based on Reinforcement Learning," Journal of System Simulation: Vol. 34: Iss. 10, Article 16.
DOI: 10.16182/j.issn1004731x.joss.21-0632
Available at: https://dc-china-simulation.researchcommons.org/journal/vol34/iss10/16

First Page

2264

Revised Date

2021-09-12

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.21-0632

Last Page

2271

CLC

TP273.2

Recommended Citation

Da Jiang, Zhiqin Cai, Zhongzhen Liu, Haijun Peng, Zhigang Wu. Reinforcement-learning-based Adaptive Tracking Control for a Space Continuum Robot Based on Reinforcement Learning[J]. Journal of System Simulation, 2022, 34(10): 2264-2271.

Corresponding Author

Zhiqin Cai,zhqcai@dlut.edu.cn

DOI

10.16182/j.issn1004731x.joss.21-0632