A sliding mode controller with neural network and fuzzy logic

A sliding mode controller with a neural network and a fuzzy boundary layer is proposed. A multilayer neural network is used for constructing the inverse identifier which is an observer of the uncertainties of a system. Also, a fuzzy boundary layer is introduced to make the continuous control input of the sliding mode controller combined with the neural inverse identifier. The proposed control scheme not only reduces the effort for finding the unknown dynamics of a system but also alleviates the chattering problems of the control input. Computer simulation reveals that the proposed approach is effective to alleviate the chattering problem of the control input