Stable Backstepping Sliding Mode Control Based on ANFIS2 for a Class of Nonlinear Systems

This paper presents an intelligent backstepping sliding mode control for a class of nonlinear systems. A new Adaptive Neuro Fuzzy Inference System (ANFIS), based on type-2 fuzzy sets (called ANFIS2) is used to approximate the conventional sliding mode control law. The proposed ANFIS2 method does not require prior information about the system; it also identifies the system's dynamics, as well as the estimated dynamics, used in the sliding mode controller. Moreover, the proposed ANFIS2 sliding mode control system - by tracking the control system's structure in the presence of uncertainty in a class of nonlinear systems - approximates the system's mathematical model momentarily. In order to compensate the control signal and to offer a better performance, a combination of a type-2 fuzzy system, backstepping method and sliding mode control is proposed. The backstepping method is used to improve the final threshold stability; and the sliding mode control is used to obtain robust response to uncertainty. The simulation results show that the proposed ANFIS2-based sliding mode control has better performance than the ANFIS-based one.