Collaborative Control for Multimanipulator Systems With Fuzzy Neural Networks

被引：16
作者：
Zhang, Jiazheng [1 ,2 ]
Jin, Long [1 ,2 ]
Wang, Yang [3 ]
机构：
[1] Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China
[2] Sci & Technol Commun Networks Lab, Shijiazhuang 050000, Peoples R China
[3] Chongqing Univ Posts & Telecommun, Sch Commun & Informat Engn, Chongqing 400000, Peoples R China
来源：
IEEE TRANSACTIONS ON FUZZY SYSTEMS | 2023年 / 31卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Manipulators; Collaboration; Task analysis; Kinematics; Fuzzy logic; Robots; Trajectory; Fuzzy logic system; multiple manipulators; neural networks; quadratic programming; DESIGN; MANIPULATORS; MODEL;
D O I：
10.1109/TFUZZ.2022.3198855
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This article develops a fuzzy-neural controller for the kinematic and collaborative control of multimanipulator systems. The entire control scheme is designed based on quadratic programming and implemented by a constructed fuzzy-neural controller. A hybrid minimum joint velocity-acceleration index is introduced to adjust the operating performance of each manipulator and reduce the kinetic energy consumption of the system. Besides, a simple but effective set of membership functions and rules are used to describe the variation of controller parameters caused by the operational complexity and vagueness during task executions. The stability and robustness of the controller are verified through theoretical analysis. Finally, simulations and experimental studies of the multimanipulator system are carried out supporting the practicality of our findings.
引用
收藏
页码：1305 / 1314
页数：10
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