Adaptive RBFNN Based Fuzzy Sliding Mode Control for Two Link Robot Manipulator

Abstract

A adaptive Radial basis function neural network (RBFNN) based fuzzy sliding mode control scheme for two link robot manipulator is proposed in this paper. In the scheme, RBFNN is used to approximate system dynamic, the weights of the RBFNN are changed according to adaptive algorithm to ensure the system state hitting the sliding surface and sliding along it. In order to guarantee the stability and the convergence of the system, the sliding mode control gain is adjusted by the adaptive fuzzy systems to compensate the network approximation error and the external disturbances. The simulation results demonstrate that the control scheme is effective.