Fuzzy sliding mode controller with RBF neural network for robotic manipulator trajectory tracking

Abstract

This paper proposes a fuzzy sliding mode controller with radial basis function neural network (RBFNN) for trajectory tracking of robot manipulator. The main problem of sliding mode controllers is that a whole knowledge of the system dynamics and system parameters is required to compute the equivalent control. In this paper, a RBFNN is proposed to compute the equivalent control. Computer simulations of three link robot manipulator for trajectory tracking indicate that the proposed method is a good candidate for trajectory control applications.