ROBUST NEURO-FUZZY SLIDING MODE CONTROLLER FOR A FLEXIBLE ROBOT MANIPULATOR

Khedoudja Kherraz, Mustapha Hamerlain, and Nouara Achour

Keywords

Flexible robot manipulator, sliding mode, neurofuzzy, chattering, trajectory control, super twisting algorithm

Abstract

In most of robotic applications, trajectory tracking control and vibration suppression in flexible link manipulator is a recurring problem, due to unknown nonlinearities and strong coupling often caused by the presence of flexibility in the links. In order to solve this problem, a new sliding mode controller using neural network and fuzzy logic is presented in this paper. The stability of the proposed controller is proved with the Lyapunov function method. Both neural network and fuzzy logic are used to compensate the highly nonlinear system uncertainties. Then fuzzy logic is used to eliminate the chattering effect caused by the robust conventional sliding mode control. Comparative simulations show the superiority of the proposed controller regarding the Super Twisting Algorithm and confirm its robustness with respect to bounded disturbance and its ability to suppress the vibrations of the flexible link manipulator.

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