<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></abstract>

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.

A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel

Faculty of Electrical Engineering, West Pomeranian University of Technology, 26 Kwietnia 10, 71-126 Szczecin, Poland

International Journal of Applied Mathematics and Computer Science

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...

A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel

Online veröffentlicht: 30. Dez. 2015

Seitenbereich: 877 - 893

Eingereicht: 06. Okt. 2014

DOI: https://doi.org/10.1515/amcs-2015-0063

Schlüsselwörter
MIMO dynamic plant, identification, nonlinear system

© 2015 Stanisław Bańka et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel

Online veröffentlicht: 30. Dez. 2015

Seitenbereich: 877 - 893

Eingereicht: 06. Okt. 2014

DOI: https://doi.org/10.1515/amcs-2015-0063

SchlüsselwörterMIMO dynamic plant, identification, nonlinear system

© 2015 Stanisław Bańka et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
MIMO dynamic plant, identification, nonlinear system