Manoeuvring simulation of catamaran by using implicit models based on support vector machines

Abstract

Manoeuvring models based on support vector machines (SVMs) are proposed for the manoeuvring simulation of a catamaran. Implicit models of manoeuvring motion are derived from the SVM regression instead of using the traditional methods for identification of the hydrodynamic coefficients. Data obtained from full-scale trials are used for regression analysis. Disturbances induced by current and wind are estimated. At the training stage, the inputs to the SVMs are the surge speed, sway speed, yaw rate and rudder angle, while the outputs are the derivatives of the surge speed, sway speed and yaw rate, respectively. At the simulation stage a predictive model is constructed with the obtained support vectors, Lagrangian factors and a constant. The Gauss function kernel is employed in the SVMs to guarantee the performance of the approximation and the robustness of the SVM regressor. The turning circle manoeuvre is simulated based on the regression manoeuvring models. Comparisons between the trials and the simulated results are conducted to demonstrate the validity of the proposed modelling method.