The project design for steering qualities of a new ship as well as the prediction and control of its behavior when at sea may all be based on records of the motions of scale models or previous ships, or even on the observation of the particular ship in the immediate past. In recent years new techniques of stochastic system identification have appeared as alternatives to the deterministic methods hitherto applied to the analysis of free-sailing experiments. The present report covers the initial results of co-operation on ship steering problems between the Swedish State Shipbuilding Experimental Tank (SSPA) and the Lund Institute of Technology, Department of Automatic Control (LTH), where the theory of the maximum likelihood parameter estimation has earlier been developed for a variety of dynamic processes. The role of system identification within ship steering analysis is discussed, the kinematics of ships are high-lighted and the mathematical models for the ship dynamics are reformulated. The system identification complex is introduced with special emphasis on parameter identifiability and estimation, and on the requirements to be placed on input-output models.
The Identification of Linear Ship Steering Dynamics Using Maximum Likelihood Parameter Estimation
1975
107 pages
Report
Keine Angabe
Englisch
Maximum-Likelihood Parameter-Estimation Algorithm
NTRS | 1986
|MAXIMUM-LIKELIHOOD GPS PARAMETER ESTIMATION
Online Contents | 2005
|Identification of ship steering dynamics
Tema Archiv | 1976
|Parameter Estimation via Gaussian Processes and Maximum Likelihood Estimation
British Library Conference Proceedings | 2010
|