Cooperative-theoretic optimal adaptive robust control for fuzzy multiple manipulator systems

被引:2
|
作者
Wang, Faliang [1 ,2 ]
Chen, Ke [1 ]
Zhen, Shengchao [1 ,3 ]
Zheng, Hongmei [1 ]
Chen, Xiaofei [1 ]
Wang, Zhaodong [2 ]
机构
[1] Hefei Univ Technol, Sch Mech Engn, Hefei 230009, Anhui, Peoples R China
[2] Jingdezhen Univ, Sch Mech & Elect Engn, Jingdezhen 333000, Jiangxi, Peoples R China
[3] Hefei Comprehens Natl Sci Ctr, Inst Artificial Intelligence, Hefei 230009, Anhui, Peoples R China
来源
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2023年 / 360卷 / 16期
基金
中国国家自然科学基金;
关键词
ROBOT MANIPULATORS; TRACKING CONTROL; PERSPECTIVE; DYNAMICS;
D O I
10.1016/j.jfranklin.2023.09.030
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article presents the study of the trajectory tracking issue of multiple manipulators from the viewpoint of servo constraint-following. First, on the framework of Udwadia-Kalaba (U-K) theory, the tasks of (holonomic or nonholonomic) trajectory tracking control are transformed into a series of servo constraints, and a nominal control is presented to realize the servo constraint-following for the system without uncertainty. Second, consider that there exists the time-varying uncertainty in the system, which is bounded and characterized by the fuzzy set theory. An adaptive robust control (ARC) is presented to achieve tracking errors uniform boundedness (UB) and uniform ultimate boundedness (UUB). Third, cooperative game theory is employed to obtain the dual optimal control parameters of the presented controller, and the mathematical derivation is performed to verify that there exists the Pareto optimal solution. Finally, simulation results show the effectiveness of the proposed control for the trajectory tracking control of multiple manipulators. (c) 2023 The Franklin Institute. Published by Elsevier Inc. All rights reserved.
引用
收藏
页码:11760 / 11787
页数:28
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