Tractive performance prediction for intelligent air-cushion track vehicle: fuzzy logic approach

Tractive performance prediction for intelligent air-cushion track vehicle: fuzzy logic approach

Fuzzy logic approach is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –cushion system with measuring th...

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Main Authors: Hossain, Altab, Rahman, Mohammed Ataur, Mohiuddin, A. K. M., Aminanda, Yulfian
Format: Article
Language:English
Published: World Academy of Science, Engineering and Technology (W A S E T) 2010
Subjects:
TL1 Motor vehicles
Online Access:http://irep.iium.edu.my/1144/
http://irep.iium.edu.my/1144/
http://irep.iium.edu.my/1144/1/v62-30.pdf
id iium-1144
recordtype eprints
spelling iium-11442012-01-08T13:28:05Z http://irep.iium.edu.my/1144/ Tractive performance prediction for intelligent air-cushion track vehicle: fuzzy logic approach Hossain, Altab Rahman, Mohammed Ataur Mohiuddin, A. K. M. Aminanda, Yulfian TL1 Motor vehicles Fuzzy logic approach is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –cushion system with measuring the vehicle traction force (TF), motion resistance (MR), cushion clearance height (CH) and cushion pressure (CP). Sinkage measuring sensor, magnetic switch, pressure sensor, micro controller, control valves and battery are incorporated with the Fuzzy logic system (FLS) to investigate experimentally the TF, MR, CH, and CP. In this study, a comparison for tractive performance of an intelligent air cushion track vehicle has been performed with the results obtained from the predicted values of FLS and experimental actual values. The mean relative error of actual and predicted values from the FLS model on traction force, and total motion resistance are found as 5.58 %, and 6.78 % respectively. For all parameters, the relative error of predicted values are found to be less than the acceptable limits. The goodness of fit of the prediction values from the FLS model on TF, and MR are found as 0.90, and 0.98 respectively. World Academy of Science, Engineering and Technology (W A S E T) 2010 Article PeerReviewed application/pdf en http://irep.iium.edu.my/1144/1/v62-30.pdf Hossain, Altab and Rahman, Mohammed Ataur and Mohiuddin, A. K. M. and Aminanda, Yulfian (2010) Tractive performance prediction for intelligent air-cushion track vehicle: fuzzy logic approach. World Academy of Science, Engineering and Technology, 62. pp. 163-169. ISSN 1307-6884 http://www.waset.org/journals/waset/v62/v62-30.pdf
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic TL1 Motor vehicles
spellingShingle TL1 Motor vehicles
Hossain, Altab
Rahman, Mohammed Ataur
Mohiuddin, A. K. M.
Aminanda, Yulfian
Tractive performance prediction for intelligent air-cushion track vehicle: fuzzy logic approach
description Fuzzy logic approach is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –cushion system with measuring the vehicle traction force (TF), motion resistance (MR), cushion clearance height (CH) and cushion pressure (CP). Sinkage measuring sensor, magnetic switch, pressure sensor, micro controller, control valves and battery are incorporated with the Fuzzy logic system (FLS) to investigate experimentally the TF, MR, CH, and CP. In this study, a comparison for tractive performance of an intelligent air cushion track vehicle has been performed with the results obtained from the predicted values of FLS and experimental actual values. The mean relative error of actual and predicted values from the FLS model on traction force, and total motion resistance are found as 5.58 %, and 6.78 % respectively. For all parameters, the relative error of predicted values are found to be less than the acceptable limits. The goodness of fit of the prediction values from the FLS model on TF, and MR are found as 0.90, and 0.98 respectively.
format Article
author Hossain, Altab
Rahman, Mohammed Ataur
Mohiuddin, A. K. M.
Aminanda, Yulfian
author_facet Hossain, Altab
Rahman, Mohammed Ataur
Mohiuddin, A. K. M.
Aminanda, Yulfian
author_sort Hossain, Altab
title Tractive performance prediction for intelligent air-cushion track vehicle: fuzzy logic approach
title_short Tractive performance prediction for intelligent air-cushion track vehicle: fuzzy logic approach
title_full Tractive performance prediction for intelligent air-cushion track vehicle: fuzzy logic approach
title_fullStr Tractive performance prediction for intelligent air-cushion track vehicle: fuzzy logic approach
title_full_unstemmed Tractive performance prediction for intelligent air-cushion track vehicle: fuzzy logic approach
title_sort tractive performance prediction for intelligent air-cushion track vehicle: fuzzy logic approach
publisher World Academy of Science, Engineering and Technology (W A S E T)
publishDate 2010
url http://irep.iium.edu.my/1144/
http://irep.iium.edu.my/1144/
http://irep.iium.edu.my/1144/1/v62-30.pdf
first_indexed 2023-09-18T20:08:22Z
last_indexed 2023-09-18T20:08:22Z
_version_ 1777407311002730496

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