Adaptive Fuzzy Control of a Cable-Driven Parallel Robot

Mai-The Vu, Kuo-Hsien Hsia, Fayez F. M. El-Sousy, Thaned Rojsiraphisal (), Reza Rahmani and Saleh Mobayen ()
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Mai-The Vu: School of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea
Kuo-Hsien Hsia: Department of Electrical Engineering, National Yunlin University of Science and Technology, 123 University Road, Douliou 64002, Taiwan
Fayez F. M. El-Sousy: Department of Electrical Engineering, Prince Sattam Bin Abdulaziz University, Al Kharj 16278, Saudi Arabia
Thaned Rojsiraphisal: Advanced Research Center for Computational Simulation, Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
Reza Rahmani: Multidisciplinary Center for Infrastructure Engineering, Shenyang University of Technology, Shenyang 110870, China
Saleh Mobayen: Graduate School of Intelligent Data Science, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou 640301, Taiwan

Mathematics, 2022, vol. 10, issue 20, 1-16

Abstract: Cable robots are a type of parallel robot in which cables have replaced the usual rigid arms. In cable robots, due to the tensile strength of the cable, the workspace analysis is much more complex than in conventional robots. In this paper, we design an adaptive fuzzy controller for a cable-driven parallel robot (CDPR). In the proposed controller, the results show that the accuracy of the system performance in tracking the reference value as well as the controller performance speed is better than that of the robust method. In one of the simulation modes, the performance speed of the control system for convergence is reduced and its error is very small, which indicates the proper performance of the proposed adaptive fuzzy method. It should be noted that all simulations are performed in a MATLAB software environment.

Keywords: parallel robot; dynamic modeling; adaptive control; fuzzy controller; composite control (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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