Decentralized RBFNN Type-2 Fuzzy Sliding Mode Controller for Robot Manipulator Driven by Artificial Muscles

[摘要] In the few last years, investigations in neural networks, fuzzy systems and their combinations become attractive research areas for modeling and controlling of uncertain systems. In this paper, we propose a new robust controller based on the integration of a Radial Base Function Neural Network (RBFNN) and an Interval Type-2 Fuzzy Logic (IT2FLC) for robot manipulator actuated by pneumatic artificial muscles (PAM). The proposed approach was synthesized for each joint using Sliding Mode Control (SMC) and named Radial Base Function Neural Network Type-2 Fuzzy Sliding Mode Control (RBFT2FSMC). Several objectives can be accomplished using this control scheme such as: avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy control, guaranteeing the stability and the robustness of the system, and finally handling the uncertainties of the system. The proposed control approach is synthesized and the stability of the robot using this controller was analyzed u...

[学科分类] 自动化工程

[关键词] Artificial Muscle;Radial Basis Function Neural Network;Type-2 Fuzzy Logic;Sliding Mode Control;Lyapunov Stability