Parameter identification of ship model based on feedback particle filter

  Objective   In recent years, ships are becoming larger, faster and more intelligent, so the ship dynamic positioning technology is particularly important. In order to establish a kinematic mathematical model in the dynamic positioning system, we need to determine the values of the parameters in the model.

  Methods   Firstly, a dredger is used as the research object to establish the mathematical model of the ship movement, and the surge motion model and the sway and yaw motion model are extracted. The unknown parameters in the model are identified based on the system identification theory and the Feedback Particle Filter(FPF)algorithm, including the thrust coefficients of two main thrusters and one side thruster. Then, the parameters to be identified are obtained by the simulation experiment.

  Results   Finally, by comparing with the Extended Kalman Filter(EKF)algorithm, it is shown that the FPF algorithm is better at identifying the parameters and the reliability of FPF algorithm is verified.

  Conclusion   This method has good application prospect in ship dynamic positioning system.