Nonlinear Control Method For Ship Rudder Roll Stabilization System

It is known that the purpose of rudder roll stabilization is to control simultaneously the course and roll by rudder.Specifically,by utilizing the low-frequency and high-frequency steering motion,the ship course and roll motion are maintained and reduced,respectively.For the same ship,ship model parameters will be changed accordingly when the ship speed,loading and attachments are changed.Therefore,the ship motion is inherently nonlinear and uncertain.The presence of nonlinearity and uncertainty which can lead to the roll reduction rate decreased.Actuator saturation nonlinearity is one of the reasons that the performance of rudder roll control system is affected.When the system is subject to saturation,any controller output that excesses actuator saturation range cannot have any effect on the controlled object.In this case,the performance of the closed-loop system will be in a sharp decline.At the same time,frequent steering is bounded to bring great loss of steering gear.The reduction of the rudder amplitude and velocity must be considered as indicators.This thesis will be carried out based on the above-mentioned questions.The control methods of nonlinear,robust and intelligent are introduced to solve the nonlinearity,parametric uncertainty problem and actuator saturation,the wear problem of rudder roll stabilization system.An exact feedback linearization method based on closed-loop gain shaping algorithm is proposed,by in-depth analysising of ship roll and yaw joint control problem.The controllers of roll and yaw are designed.On this basis,fuzzy optimization algorithm is applied in optimization allocation the controlled rudder angles of roll and yaw.The proposed method of controller design and optimization make the parameter solving is simple,and it is suitable for engineering application.An improved analytic model predictive control method is proposed to deal with a class of bounded uncertain rudder roll stabilization system.Firstly,it can be redefined as the nominal system with uncertain model,and the optimal control law with uncertainties is obtained.Derivation shows that the obtained control law is bounded and the analytic model predictive control that eliminates uncertainties is then able to acquire utilizing the boundary value.The controller can be realized without extra compensation of uncertainties in the process of controlling nonlinear systems.The simulation results show that,the validity of the proposed method is verified.A fuzzy adaptive analytic model predictive control method based on Moore-Penrose inverse is proposed in this paper for a class of uncertain nonlinear rudder roll stabilization systems.Specifically,invoking the standard results from the Moore-Penrose inverse of matrix,the unmatched problem which exists commonly in input and output dimensions of systems is firstly solved.Using fuzzy systems can uniformly approximate the uncertainties of predictive control law,weight coefficients of fuzzy system is adjusted online according to the feedback error of system.To further reduce the impact of fuzzy approximation error on the system and improve the robustness of the system,the robust compensation term is introduced.It is proved that the closed-loop system is uniformly ultimately bounded by Lyapunov stability theory.A class of dual-loop anti-windup compensator which contains traditional anti-windup compensator and delay anti-windup compensator is designed by optimizing actuator saturation occurs before feedback to the controller state error integral performance indicators,for rudder roll stabilization control systems with actuator saturation.When the system has high saturation with these dual-loop anti-windup compensators,it can weaken the influence of saturation to system performance significantly.