Identification of fractional-order dynamical systems based on nonlinear function optimization

In general, real objects are fractional-order systems and also dy- namical processes taking place in them are fractional-order processes, although in some types of systems the order is very close to an integer order. So we con- sider dynamical system whose mathematical description is a differential...

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Main Authors: Dorćak, Luboḿir, Gonzalez, Emmanuel A., Terṕak, J́an, Valsa, Juraj, Pivka, Ladislav
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Published: Animo Repository 2013
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/3006
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-40052021-11-19T03:11:44Z Identification of fractional-order dynamical systems based on nonlinear function optimization Dorćak, Luboḿir Gonzalez, Emmanuel A. Terṕak, J́an Valsa, Juraj Pivka, Ladislav In general, real objects are fractional-order systems and also dy- namical processes taking place in them are fractional-order processes, although in some types of systems the order is very close to an integer order. So we con- sider dynamical system whose mathematical description is a differential equa- tion in which the orders of derivatives can be real numbers. With regard to this, in the task of identification, it is necessary to consider also the fractional order of the dynamical system. In this paper we give suitable numerical solutions of differential equations of this type and subsequently an experimental method of identification in the time domain is given. We will concentrate mainly on the identification of parameters, including the orders of derivatives, for a chosen structure of the dynamical model of the system. Under mentioned assump- tions, we would obtain a system of nonlinear equations to identify the system. More suitable than to solve the system of nonlinear equations is to formulate the identification task as an optimization problem for nonlinear function mini- mization. As a criterion we have considered the sum of squares of the vertical deviations of experimental and theoretical data and the sum of squares of the corresponding orthogonal distances. The verification was performed on systems with known parameters and also on a laboratory object. 2013-12-19T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/3006 Faculty Research Work Animo Repository Fractional calculus Least squares Nonlinear functional analysis Time-domain analysis Electric controllers Electrical and Electronics
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Fractional calculus
Least squares
Nonlinear functional analysis
Time-domain analysis
Electric controllers
Electrical and Electronics
spellingShingle Fractional calculus
Least squares
Nonlinear functional analysis
Time-domain analysis
Electric controllers
Electrical and Electronics
Dorćak, Luboḿir
Gonzalez, Emmanuel A.
Terṕak, J́an
Valsa, Juraj
Pivka, Ladislav
Identification of fractional-order dynamical systems based on nonlinear function optimization
description In general, real objects are fractional-order systems and also dy- namical processes taking place in them are fractional-order processes, although in some types of systems the order is very close to an integer order. So we con- sider dynamical system whose mathematical description is a differential equa- tion in which the orders of derivatives can be real numbers. With regard to this, in the task of identification, it is necessary to consider also the fractional order of the dynamical system. In this paper we give suitable numerical solutions of differential equations of this type and subsequently an experimental method of identification in the time domain is given. We will concentrate mainly on the identification of parameters, including the orders of derivatives, for a chosen structure of the dynamical model of the system. Under mentioned assump- tions, we would obtain a system of nonlinear equations to identify the system. More suitable than to solve the system of nonlinear equations is to formulate the identification task as an optimization problem for nonlinear function mini- mization. As a criterion we have considered the sum of squares of the vertical deviations of experimental and theoretical data and the sum of squares of the corresponding orthogonal distances. The verification was performed on systems with known parameters and also on a laboratory object.
format text
author Dorćak, Luboḿir
Gonzalez, Emmanuel A.
Terṕak, J́an
Valsa, Juraj
Pivka, Ladislav
author_facet Dorćak, Luboḿir
Gonzalez, Emmanuel A.
Terṕak, J́an
Valsa, Juraj
Pivka, Ladislav
author_sort Dorćak, Luboḿir
title Identification of fractional-order dynamical systems based on nonlinear function optimization
title_short Identification of fractional-order dynamical systems based on nonlinear function optimization
title_full Identification of fractional-order dynamical systems based on nonlinear function optimization
title_fullStr Identification of fractional-order dynamical systems based on nonlinear function optimization
title_full_unstemmed Identification of fractional-order dynamical systems based on nonlinear function optimization
title_sort identification of fractional-order dynamical systems based on nonlinear function optimization
publisher Animo Repository
publishDate 2013
url https://animorepository.dlsu.edu.ph/faculty_research/3006
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