Ship's tracking control based on nonlinear time series model

For actualization of ship tracking control along a desired path with a constant velocity, a hybrid model is proposed to represent the ship's tracking dynamic behavior. Firstly, a single-input single-output nonlinear time series model is built for characterizing the responses between the ship's heading angle deviation and its rudder angle. To represent nonlinearity of the ship motion, the rolling angle is used as the model index to make the model parameters vary with the ship sailing states considering the yaw-heel-effect. The nonlinear time series model is identified offline by using previously observed real data. Then, a state-space model combined with the relationship between the heading angle deviations and the cross track errors is proposed to represent the tracking dynamic behavior. On the basis of the identified state-space type tracking motion model, a predictive controller is designed to steer the ship sailing forward with the constant velocity along the predefined reference path. The effectiveness of the nonlinear time series model-based method for the tracking control proposed in this paper is demonstrated by simulation studies and actual experiments.

► A nonlinear time series model is proposed to represent a ship tracking dynamics.
► A model predictive controller is designed for ship tracking control.
► A navigation strategy is proposed for the controller.
► Onboard experiments were conducted and showed a good control performance.