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 is used to track control design in the presence of uncertainty in a class of nonlinear systems. 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.
Key words: Sliding mode control; Adaptive neuro fuzzy inference system; ANFIS2; Backstepping control; Stability analysis.
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