Nonlinear Backstepping Design of Ship Steering Controller: Using Unscented Kalman Filter to Estimate the Uncertain Parameters

This paper proposes an unscented Kalman filter(UKF) based steering controller to force underactuated nonlinear autonomous ships to follow a reference path under constant disturbances induced by wave, wind and ocean-current. By using Nomoto ship model with nonlinear maneuvering characteristics and backstepping design methodology, a nonlinear ship steering controller is designed successfully. The UKF is used to update the estimation of the uncertain parameters online to avoid the parameters´ drift due to time-varying added mass matrices. MATLAB simulation shows that the presented algorithm can overcome the nonlinear specialities successfully and achieve better tracking effect.