Study On Course Intelligent Control And Simulation For Large Container Ship

Container vessels as the main tool for maritime transport with large-scale, high-speed characteristics. With the increase in the density of marine transportation, it is a challenge that maintain the ship navigation safety and economy. So, it is important that a large ship has good maneuverability and heading control capacity, in order to ensure the safe navigation of ships and reduce.From the MMG model, constructed the response of nonlinear ship model based on the input and output. This model is relatively simple, but also to meet the requirements of simulation accuracy. Analysis of the impact of the marine environment of ships sailing and establish a mathematical model of the equivalent rudder angle of the wind, waves and currents, and other outside interference.Discussed the Active disturbance rejection controller(ADRC) based on the shortcomings of classical PID. Introduce the three components of the ADRC controller, and various parts of the parameter tuning analysis, gives a general parameter tuning method.The research of ship course control is based on two large containers. Discussed annal parameters of PID controller and ADRC controller for ship course control, and the simulation results show that ADRC controller has good handing performance and maintain a stable course of performance under adverse sea conditions. From the simulation result of two different ships, it is obviously that ADRC controller has good versatility within a certain range for different ships.For the parameters of ADRC controllers,tuning difficult shortcomings, design a single neural network, use the self-learning and adaptive function of a single neural to realize the parameters of the ADRC controllers on-line-self-tuning, and test it through ulation result. Finally, try a multi-modal control methods is introduced to the ship heading control, and look forward to receiving a response speed is fast enough, but also has good robustness and quality of the course controller. Switch control and single neural ADRC controllers into multi-modal control strategies, design the controller, and the simulation show that the effectiveness of the multi-modal controller.