A statistical modeling and tracking control approach to marine vehicle

For actualization of ship tracking control along a desired path with constant velocity, a statistical modeling method is proposed to represent the tracking dynamic behavior of ship. Firstly, a SISO RBF-ARX model is built for characterizing ship motion between heading angle deviation and rudder angle of ship. To represent ship motion´s nonlinearity, rolling angle is used as the RBF-ARX model index to make the model parameters vary with ship moving state. The RBF-ARX model is identified off-line by using previously observed real data. Then, a state space model combined with the relationship between heading angle deviation and position tracking error of ship is proposed to represent ship tracking motion behavior. On the basis of the identified ship´s state-space type tracking motion model, a predictive controller is designed to steer ship moving forward with constant velocity along a predefined reference path. The effectiveness of the modeling and control methods proposed in this paper is demonstrated by the tracking control simulation in which the modeling data is observed from a real experimental ship.