Collaborative Control for Multimanipulator Systems With Fuzzy Neural Networks

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 i...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems 2023-04, Vol.31 (4), p.1305-1314
Main Authors: Zhang, Jiazheng, Jin, Long, Wang, Yang
Format: Article
Language:English
Subjects:
Acceleration
Artificial neural networks
Collaboration
Control systems
Controllers
Energy consumption
Fuzzy control
Fuzzy logic
Fuzzy logic system
Fuzzy systems
Kinematics
Kinetic energy
Manipulators
multiple manipulators
neural networks
Quadratic programming
Robots
Robust control
Stability analysis
Task analysis
Trajectory
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Summary: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.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2022.3198855