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Modelling and analysis of all terrain vehicle (ATV) using system identification for yaw stability

This paper presents the modelling and analysis of path-following planning motion of an All-Terrain Vehicle (ATV) using system identification technique in term of yaw stability. The modelling is based on the single track and established by using Newtonian equation motion. Mathematical modelling is co...

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主要な著者: Abd Azis, Fadilah, Mohd Aras, Mohd Shahrieel, Ab Rashid, Mohd Zamzuri, Othman, Muhammad Nur, Khamis, K.S., Ghani, O.A.A.
フォーマット: 論文
言語:English
出版事項: Trans Tech Publications, Switzerland 2015
主題:
TJ Mechanical engineering and machinery
オンライン･アクセス:http://eprints.utem.edu.my/id/eprint/14321/1/AMM.761.221.pdf
http://eprints.utem.edu.my/id/eprint/14321/
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spelling my.utem.eprints.143212015-05-28T04:37:35Z http://eprints.utem.edu.my/id/eprint/14321/ Modelling and analysis of all terrain vehicle (ATV) using system identification for yaw stability Abd Azis, Fadilah Mohd Aras, Mohd Shahrieel Ab Rashid, Mohd Zamzuri Othman, Muhammad Nur Khamis, K.S. Ghani, O.A.A. TJ Mechanical engineering and machinery This paper presents the modelling and analysis of path-following planning motion of an All-Terrain Vehicle (ATV) using system identification technique in term of yaw stability. The modelling is based on the single track and established by using Newtonian equation motion. Mathematical modelling is constructed in form of state space equation with the parameters used are measured through physical measurement of prototype ATV. Based on this model selection, the open loop system is simulated and the result will be validated by using system identification. Inertial Measurement Unit (IMU) sensor is used to collect and measure the data for the path following planning. The analysis results for yaw stability of prototype ATV are validated by system identification method with step response approach. Both of the simulated and measured data is compared and the data is estimated to get the best fit for yaw estimation by using complimentary filter technique. From the result, the best fit for yaw estimation is 91.96% and considered as stabilized at steering angle of 45°. Trans Tech Publications, Switzerland 2015-03-05 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/14321/1/AMM.761.221.pdf Abd Azis, Fadilah and Mohd Aras, Mohd Shahrieel and Ab Rashid, Mohd Zamzuri and Othman, Muhammad Nur and Khamis, K.S. and Ghani, O.A.A. (2015) Modelling and analysis of all terrain vehicle (ATV) using system identification for yaw stability. Applied Mechanics and Materials, 761 (2. pp. 221-226. ISSN 16609336 doi:10.4028/www.scientific.net/AMM.761.221
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Abd Azis, Fadilah
Mohd Aras, Mohd Shahrieel
Ab Rashid, Mohd Zamzuri
Othman, Muhammad Nur
Khamis, K.S.
Ghani, O.A.A.
Modelling and analysis of all terrain vehicle (ATV) using system identification for yaw stability
description This paper presents the modelling and analysis of path-following planning motion of an All-Terrain Vehicle (ATV) using system identification technique in term of yaw stability. The modelling is based on the single track and established by using Newtonian equation motion. Mathematical modelling is constructed in form of state space equation with the parameters used are measured through physical measurement of prototype ATV. Based on this model selection, the open loop system is simulated and the result will be validated by using system identification. Inertial Measurement Unit (IMU) sensor is used to collect and measure the data for the path following planning. The analysis results for yaw stability of prototype ATV are validated by system identification method with step response approach. Both of the simulated and measured data is compared and the data is estimated to get the best fit for yaw estimation by using complimentary filter technique. From the result, the best fit for yaw estimation is 91.96% and considered as stabilized at steering angle of 45°.
format Article
author Abd Azis, Fadilah
Mohd Aras, Mohd Shahrieel
Ab Rashid, Mohd Zamzuri
Othman, Muhammad Nur
Khamis, K.S.
Ghani, O.A.A.
author_facet Abd Azis, Fadilah
Mohd Aras, Mohd Shahrieel
Ab Rashid, Mohd Zamzuri
Othman, Muhammad Nur
Khamis, K.S.
Ghani, O.A.A.
author_sort Abd Azis, Fadilah
title Modelling and analysis of all terrain vehicle (ATV) using system identification for yaw stability
title_short Modelling and analysis of all terrain vehicle (ATV) using system identification for yaw stability
title_full Modelling and analysis of all terrain vehicle (ATV) using system identification for yaw stability
title_fullStr Modelling and analysis of all terrain vehicle (ATV) using system identification for yaw stability
title_full_unstemmed Modelling and analysis of all terrain vehicle (ATV) using system identification for yaw stability
title_sort modelling and analysis of all terrain vehicle (atv) using system identification for yaw stability
publisher Trans Tech Publications, Switzerland
publishDate 2015
url http://eprints.utem.edu.my/id/eprint/14321/1/AMM.761.221.pdf
http://eprints.utem.edu.my/id/eprint/14321/
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score 13.251813

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