Research On Ship Course RANN Control With Specified Steady-state Performance

The development of the shipbuilding has been in full swing in recent decades,which makes the ship develop in the direction of scale,advanced and specialization,while the core concept of the development of ship is always the control performance of ship course without the diversification ship development direction.Therefore,how to improve this performance need to be further researched.Targeted control strategies are proposed to complete effective control of the system,which can deal with the uncertainties effectively in the ship course keeping system,including system drift uncertainty,control gain uncertainty,and interference in the unknown environment of sea.Firstly,RBF neural network approximation method was used to process the drift uncertainty and unknown external interference in the system.A RANN(Robust Adaptive Neural Network)controller was designed,which is suitable for ship course keeping control system,based on Backstepping technology and Lyapunov stability theory.This controller makes all the signals in the closed-loop system uniformly and ultimately bounded,and the tracking error of the system eventually converges to the preset stabilization boundary.Secondly,in order to solve the problem of unknown control direction in actual ship engineering,a RANN(Robust Adaptive Neural Network)controller is programmed,which can effectively deal with the unknown control gain sign of the system and the problem of the prescribed transient and steady control performance,by introducing Nussbaum gain technology and constructing a new Nussbaum function.The controller can also make all the signals in the closed-loop system uniformly and ultimately bounded,and the tracking error of the system eventually converges to the preset stabilization boundary.Finally,the effectiveness of the designed controller was verified through the simulation research in MATLAB.