A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel
, , and | Dec 30, 2015
International Journal of Applied Mathematics and Computer Science
Special issue: Complex Problems in High-Performance Computing Systems, Editors: Mauro Iacono, Joanna Kołodziej
Published Online: Dec 30, 2015
Page range: 877 - 893
Received: Oct 06, 2014
DOI: https://doi.org/10.1515/amcs-2015-0063
Keywords
© 2015 Stanisław Bańka et al., published by De Gruyter Open
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
The paper presents algorithms for parameter identification of linear vessel models being in force for the current operating point of a ship. Advantages and disadvantages of gradient and genetic algorithms in identifying the model parameters are discussed. The study is supported by presentation of identification results for a nonlinear model of a drilling vessel.