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

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 id...

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Main Authors:	Bańka Stanisław, Brasel Michał, Dworak Paweł, Jaroszewski Krzysztof
Format:	Article
Language:	English
Published:	Sciendo 2015-12-01
Series:	International Journal of Applied Mathematics and Computer Science
Subjects:	mimo dynamic plant identification nonlinear system
Online Access:	https://doi.org/10.1515/amcs-2015-0063

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spelling	doaj-3226f83cb1534350b077f5b5f0b63f442021-09-06T19:39:49ZengSciendoInternational Journal of Applied Mathematics and Computer Science2083-84922015-12-0125487789310.1515/amcs-2015-0063amcs-2015-0063A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling VesselBańka Stanisław0Brasel Michał1Dworak Paweł2Jaroszewski Krzysztof3Faculty of Electrical Engineering, West Pomeranian University of Technology, 26 Kwietnia 10, 71-126 Szczecin, PolandFaculty of Electrical Engineering, West Pomeranian University of Technology, 26 Kwietnia 10, 71-126 Szczecin, PolandFaculty of Electrical Engineering, West Pomeranian University of Technology, 26 Kwietnia 10, 71-126 Szczecin, PolandFaculty of Electrical Engineering, West Pomeranian University of Technology, 26 Kwietnia 10, 71-126 Szczecin, PolandThe 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.https://doi.org/10.1515/amcs-2015-0063mimo dynamic plantidentificationnonlinear system
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Bańka Stanisław Brasel Michał Dworak Paweł Jaroszewski Krzysztof
spellingShingle	Bańka Stanisław Brasel Michał Dworak Paweł Jaroszewski Krzysztof A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel International Journal of Applied Mathematics and Computer Science mimo dynamic plant identification nonlinear system
author_facet	Bańka Stanisław Brasel Michał Dworak Paweł Jaroszewski Krzysztof
author_sort	Bańka Stanisław
title	A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel
title_short	A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel
title_full	A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel
title_fullStr	A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel
title_full_unstemmed	A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel
title_sort	comparative and experimental study on gradient and genetic optimization algorithms for parameter identification of linear mimo models of a drilling vessel
publisher	Sciendo
series	International Journal of Applied Mathematics and Computer Science
issn	2083-8492
publishDate	2015-12-01
description	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.
topic	mimo dynamic plant identification nonlinear system
url	https://doi.org/10.1515/amcs-2015-0063
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A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel

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