Design a New Intelligent Control for a Class of Nonlinear Systems

Abstract

This paper presents a new method based on computational intelligence for precise control of a class of nonlinear systems. In this method, the Radial Basis Function Neural Networks (RBFNN) is used to approximate the uncertain functions in the system dynamics. In addition, a constraint is considered on the input. The Backstepping method is used for improving the overall accuracy of the control process. To evaluate the performance of the proposed method, a single-link robot arm with nonlinear dynamics and input saturation constraint is investigated. The simulation results show the performance of the proposed method.