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...
保存先:
第一著者: | |
---|---|
フォーマット: | 学位論文 |
言語: | English |
出版事項: |
2015
|
主題: | |
オンライン・アクセス: | 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 |
タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
id |
my.utm.53841 |
---|---|
record_format |
eprints |
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 |
13.251813 |