In this paper the stochastic parameters describing the nonlinear ocean vessel steering model are identified, resorting to an Extended Kalman Filter. The proposed method is applied to a second order modified Nomoto model for the vessel navigation that is derived from first physics principles. The results obtained resorting to a realistic numerical simulator for the nonlinear vessel steering model considered are illustrated in this study.
Abstract
The paper presents an experimental method to estimate dynamic parameters of general mechanisms. The signals of dynamic motion and external force of mechanisms were obtained by a piezo-electric accelerometer and a hammer force transducer. A set of linear dynamic parameter equations are derived from nonlinear motion equations and constraint equations of mechanisms to estimate the dynamic parameters of the system. The accuracy of the parameter estimation depends on the number of non-zero singular values and the condition number of the parameter equations. A typical four-bar linkage was taken as an example for accuracy analysis of the dynamic parameter estimation.
Dynamic parameter estimation of Analog to Digital Converter with multipoint Interpolation technique
