Fuzzy sliding mode controller with neural network for robot manipulators

This paper presents an approach of cooperative control that is based on the concept of combining neural networks and the methodology of fuzzy sliding mode control (SMC). The aim of this study is to overcome some of the difficulties of conventional control methods such as controllers requires system dynamics in detailed. In the proposed control system, a neural network (NN) is developed to mimic the equivalent control law in the SMC. The structure of the NN that estimates the equivalent control is a standard two layer feed-forward NN with the backprobagation algorithm. The weights of the NN are updated such that the corrective control term of the SMC goes to zero.