In this paper, a problem of autonomous ship utility model identification for control purposes is considered. In particular, the problem is formulated in terms of model parameter estimation (one-step-ahead prediction). This is a complex task due to lack of measurements of the parameter values, their time-variability and structural uncertainty introduced by the available models. In this work, authors consider and compare two utility models based on often utilised ship model structures with time-varying parameters identified recursively using the extended Kalman lter (EKF). The validation results have been obtained using simulation experiments in which the required information for the parameter estimation task had been generated using a cognitive model of B-481 ship. The results indicate the benefits and drawbacks, in terms of estimation accuracy and computational complexity, of using each of the investigated utility model structures.
Autonomous Ship Utility Model Parameter Estimation Utilising Extended Kalman Filter
Advs in Intelligent Syst., Computing
24.06.2020
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Parameter Estimation of Maneuvering Variables of SIGMA-Extended War Ship Using Kalman Filter
Trans Tech Publications | 2018
|Dual extended Kalman filter for vehicle state and parameter estimation
Online Contents | 2006
|Dual extended Kalman filter for vehicle state and parameter estimation
Kraftfahrwesen | 2006
|Dual extended Kalman filter for vehicle state and parameter estimation
Taylor & Francis Verlag | 2006
|