The Research Of A Algorithm Of Ship Adaptive Autopilot

The automatic control of the ship heading is an important indicator of ship maneuvering performance, and it is closely related with ship navigation safety and economy. With the growing demand of China’s shipping, ship course automatic control are increasingly high requirements. This thesis focusing on a practical ship adaptive autopilot applies the model reference adaptive system and optimal control theory to design a control algorithm, and simulate steering engine servo control system.The subject designs ship course optimal PD controller based on optimal control theory, using the first-order model of Nomoto ship equations. The selected performance index coordinates the contradiction between the heading accuracy and energy loss, and the parameter in it can be adjusted according to the weather and sea conditions, so it has a ability to adapt to changes in the weather. Kalman filter algorithm is applied to the adaptive identification of the ship model parameters based on model reference adaptive theory, and compensate model parameters for changes of the ship speed to improve the accuracy of parameter identification. And first-order low-pass filter and the Kalman filter filter out high-frequency sea wave interference in the rudder angle and heading signals.The program has the advantages of speed, accuracy, energy saving, security, adaptability, etc.. Course-keeping autopilot provides an effective solution to achieve indirect track-keeping and integrated bridge control systems.