Collaborative Control for Multimanipulator Systems With Fuzzy Neural Networks
Jiazheng Zhang, Long Jin, Yang Wang
Abstract
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.