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Optimal composite nonlinear feedback control with multi objective algorithms for active front steering system

The main purpose of controlling vehicle handling is to ensure that the vehicle follows the desired path. Vehicle yaw rate must be controlled in order to achieve a good vehicle handling. In this thesis, optimal Composite Nonlinear Feedback (CNF) controller with multi objective algorithms is proposed...

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Main Author: Ramli, Liyana
Format: Thesis
Language:English
Published: 2015
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/53841/1/LiyanaRamliMFKE2015.pdf
http://eprints.utm.my/id/eprint/53841/
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spelling my.utm.538412020-09-07T02:59:09Z http://eprints.utm.my/id/eprint/53841/ Optimal composite nonlinear feedback control with multi objective algorithms for active front steering system Ramli, Liyana TK Electrical engineering. Electronics Nuclear engineering The main purpose of controlling vehicle handling is to ensure that the vehicle follows the desired path. Vehicle yaw rate must be controlled in order to achieve a good vehicle handling. In this thesis, optimal Composite Nonlinear Feedback (CNF) controller with multi objective algorithms is proposed for the Active Front Steering (AFS) system in improving the vehicle yaw rate response. The model used to validate the performance of the controller is a 7 degree-of-freedom (DOF) nonlinear vehicle model. This vehicle model is also simplified to a 2 DOF bicycle model for the purpose of controller design. In designing the optimal CNF control, the parameter selection of optimal linear and non-linear gain parameters becomes very important to obtain a good system response. Optimization algorithms are utilized to minimize the complexity in selecting the best parameters. Hence, Multi Objective Particle Swarm Optimization (MOPSO) and Multi Objective Genetic Algorithm (MOGA) are proposed to produce the optimal CNF. Moreover, manual tuning method was utilized and has been compared with the proposed algorithms. As a result, the performance of the yaw rate response is improved with a 98 percent reduction in error. Hence, the vehicle handling can be improved and the vehicle will be able to travel safely on the desired path. 2015-08 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/53841/1/LiyanaRamliMFKE2015.pdf Ramli, Liyana (2015) Optimal composite nonlinear feedback control with multi objective algorithms for active front steering system. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:86041
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
Optimal composite nonlinear feedback control with multi objective algorithms for active front steering system
description The main purpose of controlling vehicle handling is to ensure that the vehicle follows the desired path. Vehicle yaw rate must be controlled in order to achieve a good vehicle handling. In this thesis, optimal Composite Nonlinear Feedback (CNF) controller with multi objective algorithms is proposed for the Active Front Steering (AFS) system in improving the vehicle yaw rate response. The model used to validate the performance of the controller is a 7 degree-of-freedom (DOF) nonlinear vehicle model. This vehicle model is also simplified to a 2 DOF bicycle model for the purpose of controller design. In designing the optimal CNF control, the parameter selection of optimal linear and non-linear gain parameters becomes very important to obtain a good system response. Optimization algorithms are utilized to minimize the complexity in selecting the best parameters. Hence, Multi Objective Particle Swarm Optimization (MOPSO) and Multi Objective Genetic Algorithm (MOGA) are proposed to produce the optimal CNF. Moreover, manual tuning method was utilized and has been compared with the proposed algorithms. As a result, the performance of the yaw rate response is improved with a 98 percent reduction in error. Hence, the vehicle handling can be improved and the vehicle will be able to travel safely on the desired path.
format Thesis
author Ramli, Liyana
author_facet Ramli, Liyana
author_sort Ramli, Liyana
title Optimal composite nonlinear feedback control with multi objective algorithms for active front steering system
title_short Optimal composite nonlinear feedback control with multi objective algorithms for active front steering system
title_full Optimal composite nonlinear feedback control with multi objective algorithms for active front steering system
title_fullStr Optimal composite nonlinear feedback control with multi objective algorithms for active front steering system
title_full_unstemmed Optimal composite nonlinear feedback control with multi objective algorithms for active front steering system
title_sort optimal composite nonlinear feedback control with multi objective algorithms for active front steering system
publishDate 2015
url http://eprints.utm.my/id/eprint/53841/1/LiyanaRamliMFKE2015.pdf
http://eprints.utm.my/id/eprint/53841/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:86041
_version_ 1677781103582117888
score 13.211869

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