Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques

An essential step towards the solution of many scientific problems is to accomplish modelling and identification of the system under investigation. This paper endeavours to establish an empirical relationship between input and observed output data for the identification of a one-degree-of-freedom h...

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Main Authors:	Toha, Siti Fauziah, Tokhi, M. O.
Format:	Article
Language:	English
Published:	Sage Publications Ltd, London, UK 2010
Subjects:	TL500 Aeronautics
Online Access:	http://irep.iium.edu.my/5281/ http://irep.iium.edu.my/5281/ http://irep.iium.edu.my/5281/ http://irep.iium.edu.my/5281/1/JAERO_FinalCopy.pdf

id	iium-5281
recordtype	eprints
spelling	iium-52812012-10-02T00:18:03Z http://irep.iium.edu.my/5281/ Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques Toha, Siti Fauziah Tokhi, M. O. TL500 Aeronautics An essential step towards the solution of many scientific problems is to accomplish modelling and identification of the system under investigation. This paper endeavours to establish an empirical relationship between input and observed output data for the identification of a one-degree-of-freedom hovering motion model of a twin rotor multi-input–multi-output system (TRMS). The TRMS can be perceived as a static test rig for an air vehicle with formidable control challenges. Therefore, modelling of aerodynamic function of the system is needed and carried out in both time and frequency domains based on observed input and output data pairs. Improved algorithms of recursive least square, genetic algorithm, and particle swarmoptimization are proposed to develop a parametric model to mimic the behaviour of the twin rotor system in hovering mode. A complete system identification procedure is carried out, from experimental design to model validation using a laboratory-scale helicopter. In this case, the identified model is characterized by a fourth-order linear auto regressive moving average structure, which describes with very high precision the hovering motion of a TRMS. Experimental results are obtained using a laboratory set-up system, confirmingthe viability and effectiveness of the proposed methodology. Sage Publications Ltd, London, UK 2010-01-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/5281/1/JAERO_FinalCopy.pdf Toha, Siti Fauziah and Tokhi, M. O. (2010) Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques. Journal of Aerospace Engineering, 224 (9). pp. 961-977. ISSN 0954-4100(print), 2041-3025(online) http://pig.sagepub.com/content/224/9/961 DOI: 10.1243/09544100JAERO706
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TL500 Aeronautics
spellingShingle	TL500 Aeronautics Toha, Siti Fauziah Tokhi, M. O. Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques
description	An essential step towards the solution of many scientific problems is to accomplish modelling and identification of the system under investigation. This paper endeavours to establish an empirical relationship between input and observed output data for the identification of a one-degree-of-freedom hovering motion model of a twin rotor multi-input–multi-output system (TRMS). The TRMS can be perceived as a static test rig for an air vehicle with formidable control challenges. Therefore, modelling of aerodynamic function of the system is needed and carried out in both time and frequency domains based on observed input and output data pairs. Improved algorithms of recursive least square, genetic algorithm, and particle swarmoptimization are proposed to develop a parametric model to mimic the behaviour of the twin rotor system in hovering mode. A complete system identification procedure is carried out, from experimental design to model validation using a laboratory-scale helicopter. In this case, the identified model is characterized by a fourth-order linear auto regressive moving average structure, which describes with very high precision the hovering motion of a TRMS. Experimental results are obtained using a laboratory set-up system, confirmingthe viability and effectiveness of the proposed methodology.
format	Article
author	Toha, Siti Fauziah Tokhi, M. O.
author_facet	Toha, Siti Fauziah Tokhi, M. O.
author_sort	Toha, Siti Fauziah
title	Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques
title_short	Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques
title_full	Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques
title_fullStr	Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques
title_full_unstemmed	Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques
title_sort	parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques
publisher	Sage Publications Ltd, London, UK
publishDate	2010
url	http://irep.iium.edu.my/5281/ http://irep.iium.edu.my/5281/ http://irep.iium.edu.my/5281/ http://irep.iium.edu.my/5281/1/JAERO_FinalCopy.pdf
first_indexed	2023-09-18T20:13:47Z
last_indexed	2023-09-18T20:13:47Z
_version_	1777407652389715968

Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques

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