System Identification of Nonlinear Vessel Steering

Abstract

In this paper, the stochastic parameters describing a nonlinear ocean vessel steering model are identified, resorting to an extended Kalman filter (EKF). The proposed method is applied to a secondorder modified Nomoto model for vessel steering and that is derived from first physics principles. Furthermore, the results obtained resorting to a realistic numerical simulator of nonlinear vessel steering are also illustrated in this study.