Neural Networks Adaptive DSC Design of Nonlinear Systems in the Presence of Input Saturation and External Disturbance

Abstract

This paper offers a robust adaptive control based dynamic surface control for uncertain nonlinear systems in the presence of actuator saturation and external disturbance. Radial Basis Function Neural Networks are used for approximating uncertain nonlinearities. Using dynamic surface control technique, the problem of explosion of complexity caused by differentiating the virtual controllers during the recursive procedures in the conventional backstepping method is avoided. The proposed controller guarantees uniformly ultimately boundedness of the closed loop system. The effectiveness of the proposed method is illustrated with a simulation example.