Hybrid Fuzzy Sliding Mode Control for Uncertain PAM Robot Arm Plant Enhanced with Evolutionary Technique

• Main Authors: Ho Pham Huy Anh, Cao Van Kien
• Format: Article
• Language: English
• Published: Atlantis Press 2021-01-01
• Series: International Journal of Computational Intelligence Systems
• Subjects: Enhanced fuzzy sliding mode (EFSMC) controller; Pneumatic artificial muscle (PAM) robot arm; Lyapunov stability; Differential evolution (DE) technique; Uncertain nonlinear dynamic systems
• Online Access: https://www.atlantis-press.com/article/125951145/view

This paper introduces an enhanced fuzzy sliding mode control (EFSMC) algorithm used for controlling the uncertain pneumatic artificial muscle (PAM) robot arm containing external disturbances. The nonlinear features of investigated PAM robot arm system are approximated using fuzzy logic. Moreover, the coefficients of fuzzy model are optimum selected by evolutionary differential eveloution (DE) technique. The new EFSMC algorithm is designed based on the traditional sliding mode controller in which the adaptive fuzzy rule is developed based on the Lyapunov stability theory and is fuzzified with Mandani fuzzy scheme. As a consequent, the closed-loop stability of nonlinear uncertain PAM robot arm system is guaranteed to follow the global asymptotic stability. Experimental results are shown. It is evident that the proposed adaptive fuzzy rule suitable with the EFSMC controller which ensures an outperforming method in comparison with other advanced control approaches.