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Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system

The purpose of controlling the vehicle handling is to ensure that the vehicle is in a safe condition and following its desire path. Vehicle yaw rate is controlled in order to achieve a good vehicle handling. In this paper, the optimal Composite Nonlinear Feedback (CNF) control technique is proposed...

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Main Authors: Ramli, Liyana, Md. Sam, Yahaya, Mohamed, Zaharuddin, Aripin, M. Khairi, Ismail, M. Fahezal
Format: Article
Language:English
Published: Penerbit UTM Press 2015
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/58130/1/YahayaMdSam2015_CompositeNonlinearFeedbackControl.pdf
http://eprints.utm.my/id/eprint/58130/
http://dx.doi.org/10.11113/jt.v72.3877
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spelling my.utm.581302021-12-20T03:32:29Z http://eprints.utm.my/id/eprint/58130/ Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system Ramli, Liyana Md. Sam, Yahaya Mohamed, Zaharuddin Aripin, M. Khairi Ismail, M. Fahezal TK Electrical engineering. Electronics Nuclear engineering The purpose of controlling the vehicle handling is to ensure that the vehicle is in a safe condition and following its desire path. Vehicle yaw rate is controlled in order to achieve a good vehicle handling. In this paper, the optimal Composite Nonlinear Feedback (CNF) control technique is proposed for an Active Front Steering (AFS) system for improving the vehicle yaw rate response. The model used in order to validate the performance of controller is nonlinear vehicle model with 7 degree-of-freedom (DOF) and a bicycle model is implemented for the purpose of designing the controller. In designing an optimal CNF controller, the parameter estimation of linear and nonlinear gain becomes very important to produce the best output response. An intelligent algorithm is designed to minimize the time consumed to get the best parameter. To design an optimal method, Multi Objective Particle Swarm Optimization (MOPSO) is utilized to optimize the CNF controller performance. As a result, transient performance of the yaw rate has improved with the increased speed of in tracking and searching of the best optimized parameter estimation for the linear and the nonlinear gain of CNF controller. Penerbit UTM Press 2015 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/58130/1/YahayaMdSam2015_CompositeNonlinearFeedbackControl.pdf Ramli, Liyana and Md. Sam, Yahaya and Mohamed, Zaharuddin and Aripin, M. Khairi and Ismail, M. Fahezal (2015) Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system. Jurnal Teknologi, 72 . pp. 13-20. ISSN 0127-9696 http://dx.doi.org/10.11113/jt.v72.3877 DOI: 10.11113/jt.v72.3877
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Ramli, Liyana
Md. Sam, Yahaya
Mohamed, Zaharuddin
Aripin, M. Khairi
Ismail, M. Fahezal
Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system
description The purpose of controlling the vehicle handling is to ensure that the vehicle is in a safe condition and following its desire path. Vehicle yaw rate is controlled in order to achieve a good vehicle handling. In this paper, the optimal Composite Nonlinear Feedback (CNF) control technique is proposed for an Active Front Steering (AFS) system for improving the vehicle yaw rate response. The model used in order to validate the performance of controller is nonlinear vehicle model with 7 degree-of-freedom (DOF) and a bicycle model is implemented for the purpose of designing the controller. In designing an optimal CNF controller, the parameter estimation of linear and nonlinear gain becomes very important to produce the best output response. An intelligent algorithm is designed to minimize the time consumed to get the best parameter. To design an optimal method, Multi Objective Particle Swarm Optimization (MOPSO) is utilized to optimize the CNF controller performance. As a result, transient performance of the yaw rate has improved with the increased speed of in tracking and searching of the best optimized parameter estimation for the linear and the nonlinear gain of CNF controller.
format Article
author Ramli, Liyana
Md. Sam, Yahaya
Mohamed, Zaharuddin
Aripin, M. Khairi
Ismail, M. Fahezal
author_facet Ramli, Liyana
Md. Sam, Yahaya
Mohamed, Zaharuddin
Aripin, M. Khairi
Ismail, M. Fahezal
author_sort Ramli, Liyana
title Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system
title_short Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system
title_full Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system
title_fullStr Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system
title_full_unstemmed Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system
title_sort composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system
publisher Penerbit UTM Press
publishDate 2015
url http://eprints.utm.my/id/eprint/58130/1/YahayaMdSam2015_CompositeNonlinearFeedbackControl.pdf
http://eprints.utm.my/id/eprint/58130/
http://dx.doi.org/10.11113/jt.v72.3877
_version_ 1720436863955632128
score 13.211869

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