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Optimized Reduced Adaptive Fuzzy Decoupling Controller for Cobot with Disturbances Using Genetic Algorithm

Van-Truong Nguyen, Duc-Hung Nguyen, Hoang-Nam Nguyen, Nguyen-Khang Dang, Dai-Nhan Duong

2024 7th International Conference on Green Technology and Sustainable Development (GTSD)(2024)

Faculty of Mechatronics

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Abstract
This paper proposes the optimization of the reduced adaptive fuzzy decoupling control for Cobot with the presence of disturbances. In the suggested control approach, a reduced adaptive fuzzy controller is responsible for the stability and robustness of the system. Through optimization, the proposed controller not only delivers superior control effects but also has better control quality signal, learning efficiency, and minimized response time. Furthermore, the genetic algorithm is utilized to optimize oblivious parameters of the control system. The stability of the Cobot is verified through the Lyapunov theorem. Ultimately, simulations are made to perform the outstanding efficacy of the optimized reduced adaptive fuzzy controller compared to the adaptive fuzzy sets.
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Key words
Human-Robot Collaboration,Adaptive Control,Reduced Fuzzy Logic Control,Disturbances,Genetics Algorithm
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