Ant colony based model prediction of a twin rotor system

Interest in biologically-inspired optimization techniques has increased due to its accurate results, fast performance and ease of use. In this paper, an ant colony optimization (ACO) technique is deployed and used for modelling a twin rotor system. The system is perceived as a challenging engineerin...

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Main Authors: Toha, Siti Fauziah, Julai, S., Tokhi, M. Osman
Format: Article
Language:English
Published: Elsevier 2012
Subjects:
Online Access:http://irep.iium.edu.my/38671/1/ProcediaEngineering_ACO.pdf
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author Toha, Siti Fauziah
Julai, S.
Tokhi, M. Osman
author_facet Toha, Siti Fauziah
Julai, S.
Tokhi, M. Osman
author_sort Toha, Siti Fauziah
collection IIUM
description Interest in biologically-inspired optimization techniques has increased due to its accurate results, fast performance and ease of use. In this paper, an ant colony optimization (ACO) technique is deployed and used for modelling a twin rotor system. The system is perceived as a challenging engineering problem due to its strong cross coupling between horizontal and vertical axes and inaccessibility of some of its states and outputs for measurements. Accurate modelling of the system is thus required so as to achieve satisfactory control objectives. It is demonstrated that ACO can be effectively used for modelling the system with highly accurate results. The accuracy of the modelling results is demonstrated through validation tests including training and test validation and correlation tests.
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spelling oai:generic.eprints.org:386712014-10-09T08:16:57Z http://irep.iium.edu.my/38671/ Ant colony based model prediction of a twin rotor system Toha, Siti Fauziah Julai, S. Tokhi, M. Osman TL500 Aeronautics Interest in biologically-inspired optimization techniques has increased due to its accurate results, fast performance and ease of use. In this paper, an ant colony optimization (ACO) technique is deployed and used for modelling a twin rotor system. The system is perceived as a challenging engineering problem due to its strong cross coupling between horizontal and vertical axes and inaccessibility of some of its states and outputs for measurements. Accurate modelling of the system is thus required so as to achieve satisfactory control objectives. It is demonstrated that ACO can be effectively used for modelling the system with highly accurate results. The accuracy of the modelling results is demonstrated through validation tests including training and test validation and correlation tests. Elsevier 2012 Article PeerReviewed application/pdf en http://irep.iium.edu.my/38671/1/ProcediaEngineering_ACO.pdf Toha, Siti Fauziah and Julai, S. and Tokhi, M. Osman (2012) Ant colony based model prediction of a twin rotor system. Procedia Engineering, 41. pp. 1135-1144. ISSN 1877-7058 http://www.sciencedirect.com/science/article/pii/S1877705812026938 10.1016/j.proeng.2012.07.293
spellingShingle TL500 Aeronautics
Toha, Siti Fauziah
Julai, S.
Tokhi, M. Osman
Ant colony based model prediction of a twin rotor system
title Ant colony based model prediction of a twin rotor system
title_full Ant colony based model prediction of a twin rotor system
title_fullStr Ant colony based model prediction of a twin rotor system
title_full_unstemmed Ant colony based model prediction of a twin rotor system
title_short Ant colony based model prediction of a twin rotor system
title_sort ant colony based model prediction of a twin rotor system
topic TL500 Aeronautics
url http://irep.iium.edu.my/38671/1/ProcediaEngineering_ACO.pdf
work_keys_str_mv AT tohasitifauziah antcolonybasedmodelpredictionofatwinrotorsystem
AT julais antcolonybasedmodelpredictionofatwinrotorsystem
AT tokhimosman antcolonybasedmodelpredictionofatwinrotorsystem