On-and off-line identification of linear state space models

A geometrically inspired matrix algorithm is derived for the identification of state space models for multivariable linear time-invariant systems and using possibly noisy input- output measurements data only. In this project, only a limited number of input and output data are required for the determ...

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Main Author:	Khalid, Nurul Syahirah
Format:	Thesis
Language:	English
Published:	2012
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/32331/5/NurulsyahirahKhalidMFKE2012.pdf
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id	my-utm-ep.32331
record_format	uketd_dc
spelling	my-utm-ep.323312018-05-27T07:44:16Z On-and off-line identification of linear state space models 2012-01 Khalid, Nurul Syahirah TK Electrical engineering. Electronics Nuclear engineering A geometrically inspired matrix algorithm is derived for the identification of state space models for multivariable linear time-invariant systems and using possibly noisy input- output measurements data only. In this project, only a limited number of input and output data are required for the determination of the system matrices. The algorithm can be best described and also understood in the matrix formalism and consists in the following two steps. First step, a state vector sequence is realized as the intersection of the row spaces of two block Hankel matrices which is constructed by apply input - output data. Then, the system matrices are obtained at once from the least squares solution of a set of linear equations. When dealing with noisy data, this algorithm draws its excellent performance from repeated use of the numerically stable and accurate singular value decomposition. The algorithm is easily applied to slowly time-varying systems using windowing or exponential weighting. 2012-01 Thesis http://eprints.utm.my/id/eprint/32331/ http://eprints.utm.my/id/eprint/32331/5/NurulsyahirahKhalidMFKE2012.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Khalid, Nurul Syahirah On-and off-line identification of linear state space models
description	A geometrically inspired matrix algorithm is derived for the identification of state space models for multivariable linear time-invariant systems and using possibly noisy input- output measurements data only. In this project, only a limited number of input and output data are required for the determination of the system matrices. The algorithm can be best described and also understood in the matrix formalism and consists in the following two steps. First step, a state vector sequence is realized as the intersection of the row spaces of two block Hankel matrices which is constructed by apply input - output data. Then, the system matrices are obtained at once from the least squares solution of a set of linear equations. When dealing with noisy data, this algorithm draws its excellent performance from repeated use of the numerically stable and accurate singular value decomposition. The algorithm is easily applied to slowly time-varying systems using windowing or exponential weighting.
format	Thesis
qualification_level	Master's degree
author	Khalid, Nurul Syahirah
author_facet	Khalid, Nurul Syahirah
author_sort	Khalid, Nurul Syahirah
title	On-and off-line identification of linear state space models
title_short	On-and off-line identification of linear state space models
title_full	On-and off-line identification of linear state space models
title_fullStr	On-and off-line identification of linear state space models
title_full_unstemmed	On-and off-line identification of linear state space models
title_sort	on-and off-line identification of linear state space models
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2012
url	http://eprints.utm.my/id/eprint/32331/5/NurulsyahirahKhalidMFKE2012.pdf
_version_	1747815976940863488

On-and off-line identification of linear state space models

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