RBF Neural Network Control for USV with Input Saturation

Abstract

Intelligent control for USV with input saturation based on RBF network was proposed. Firstly, sliding surfaces with integral were designed on the basis of the sliding mode variable structure control technology. Secondly, RBF network was applied to approximate compensate the input saturation of system, and which was optimized by Genetic Algorithms. Finally, the control algorithm for USV was deduced by backstepping method with Lyapunov theory on the basis of sliding mode control. Relevant simulations show the control method is available for USV motion control.