Adaptive Fuzzy Design of Ship's Autopilot with Input Saturation

Abstract

This paper describes an adaptive fuzzy method used for ship's autopilot with input saturation. The ship model is described by a third order nonlinear model with unknown parameters and unknown virtual control gain function. The Takagi-Sugeno (T-S) type fuzzy systems are used to approximate unknown system functions, the adaptive fuzzy tracking controller is constructed by combining dynamic surface control (DSC) technique and the minimal-learning-parameters (MLP) algorithm. The stability analysis subject to the effect of input saturation constrains is conducted employing an auxiliary design system. With only one learning parameter and reduced computation load, the proposed algorithm can avoid both problem of "explosion of complexity" in the conventional back stepping method and singularity problem. In addition, the bounded ness stability of the closed-loop system is guaranteed and tracking error can be made arbitrary small. The effectiveness of the presented autopilot has been demonstrated in the simulation.