Robust Adaptive Control Based On Dynamic Surface Control For Ship Steering Autopilot With Uncertain Nonlinear Systems

The control problem of uncertain nonlinear system based on the dynamic surface control method is proposed, and its application to ship course controller is studied in this paper.In recent years,backstepping design method has received a great deal of attention in nonlinear robust and adaptive control.The course controller based on backstepping has good performance.However,a drawback with the backstepping technique is the problem of "explosion of complexity".That is,the complexity of controller grows drastically as the system of the order n increases.In this paper,a dynamic surface control technique is proposed to eliminate this problem by introlducing a first-order filter. The process of controller design and parameter regulation is much simpler than that constructed based on the traditional backstepping approach.The simulation results show that the adaptive course controller has good performance.By incorporating the dynamic surface technique into neural network,a novel adaptive control scheme is proposed for the ship steering's nonlinear model. By approximating the unknown nonlinear functions by radial basis function (RBF) networks,the weights and control law is realized by dynamic surface control technique. The control law can guarantee the uniformly ultimate boundedness of the solution of the closed-loop system,and make the tracking error arbitrarily small. At last, the simulation curves show that the desired results are attained.To verify the performance of the autopilot design in this paper,ship's mathematical model is researched,in consideration of the forces and moments and moments from environmental disturbances,such as winds,waves,currents,etc.By using Matlab's Simulink toolbox,simulation experiments are carried out on ship steering autopilot.