Adaptive Neural Network Based Fuzzy Sliding Mode Control of Robot Manipulator

Abstract

In this study, a fuzzy sliding mode controller based on RBFNN is proposed for robot manipulator. Fuzzy logic is used to adjust the gain of the corrective control of the sliding mode controller. The weights of the RBFNN are adjusted according to some adaptive algorithm for the purpose of controlling the system states to hit the sliding surface and then slide along it. The paper is organized as follows: In section 2 model of robot manipulator is defined. Adaptive neural network based fuzzy sliding mode controller is presented in section 3. Robot parameters and simulation results obtained for the control of three link scara robot are presented in section 4. Section 5 concludes the paper.