Fuzzy logic nonzero-sum game-based distributed approximated optimal control of modular robot manipulators with human-robot collaboration

被引：13
作者：
An, Tianjiao [1 ]
Zhu, Xinye [1 ]
Zhu, Mingchao [2 ]
Ma, Bing [1 ]
Dong, Bo [1 ]
机构：
[1] Changchun Univ Technol, Dept Control Sci & Engn, Changchun 130012, Peoples R China
[2] Chinese Acad Sci, Changchun Inst Opt Fine Mech & Phys, Changchun 130033, Peoples R China
来源：
NEUROCOMPUTING | 2023年 / 543卷
基金：
中国国家自然科学基金;
关键词：
Adaptive dynamic programming; Nonzero -sum game; Optimal control; Fuzzy systems; Modular robot manipulator; SYSTEMS; DESIGN;
D O I：
10.1016/j.neucom.2023.126276
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a fuzzy logic nonzero-sum game-based distributed approximated optimal control scheme is presented for modular robot manipulators (MRMs) with human-robot collaboration (HRC) tasks. The MRM dynamic model is formulated by using joint torque feedback (JTF) technique. Based on the differ-ential game strategy, the optimal control problem of HRC task-oriented MRM systems is transformed into a nonzero-sum game problem of multiple robotic subsystems. By taking advantage of the adaptive dynamic programming (ADP) algorithm, the distributed approximate optimal control policy under HRC tasks is developed by a novel fuzzy logic nonzero-sum game manner for solving the coupled Hamilton-Jacobian (HJ) equation. The trajectory tracking error under HRC task of the closed-loop MRM system is proved to be ultimately uniformly bounded (UUB) using the Lyapunov theory. Finally, experi-ment results have been presented, which demonstrate the advantage and effectiveness of the developed method. (c) 2023 Elsevier B.V. All rights reserved.
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页数：10
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