Power consumption prediction for an intelligent air-cushion tracked vehicle: fuzzy expert system

Power consumption prediction for an intelligent air-cushion tracked vehicle: fuzzy expert system

This paper describes the unique structure of an intelligent air-cushion system of a hybrid electrical air-cushion track vehicle working on swamp terrain. Fuzzy expert system (FES) is used in this study to control the swamp tracked vehicle’s intelligent air cushion system while it operates in the s...

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Main Authors: Hossain, Altab, Rahman, Mohammed Ataur, Mohiuddin, A. K. M., Aminanda, Yulfian
Format: Article
Language:English
Published: David Publishing, USA 2010
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://irep.iium.edu.my/17055/
http://irep.iium.edu.my/17055/
http://irep.iium.edu.my/17055/1/Power_consumption_prediction_for_an_intelligent_air-cushion.pdf
id iium-17055
recordtype eprints
spelling iium-170552012-04-02T08:02:22Z http://irep.iium.edu.my/17055/ Power consumption prediction for an intelligent air-cushion tracked vehicle: fuzzy expert system Hossain, Altab Rahman, Mohammed Ataur Mohiuddin, A. K. M. Aminanda, Yulfian TJ Mechanical engineering and machinery This paper describes the unique structure of an intelligent air-cushion system of a hybrid electrical air-cushion track vehicle working on swamp terrain. Fuzzy expert system (FES) is used in this study to control the swamp tracked vehicle’s intelligent air cushion system while it operates in the swamp peat. The system will be effective to control the intelligent air-cushion system with total power consumption (PC), cushion clearance height (CCH) and cushion pressure (CP). Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, pressure sensor, micro controller and battery pH sensor will be incorporated with the (FES) to investigate experimentally the PC, CCH and CP. In this study, we provide illustration how FES might play an important role in the prediction of power consumption of the vehicle’s intelligent air-cushion system. The mean relative error of actual and predicted values from the FES model on total power consumption is found as 10.63 %, which is found to be alomst equal to the acceptable limits of 10%. The goodness of fit of the prediction values from the FES model on PC is found as 0.97. David Publishing, USA 2010-05 Article PeerReviewed application/pdf en http://irep.iium.edu.my/17055/1/Power_consumption_prediction_for_an_intelligent_air-cushion.pdf Hossain, Altab and Rahman, Mohammed Ataur and Mohiuddin, A. K. M. and Aminanda, Yulfian (2010) Power consumption prediction for an intelligent air-cushion tracked vehicle: fuzzy expert system. Journal of Energy and Power Engineering, 4 (5). pp. 10-17. ISSN 1934-8975 http://davidpublishing.org/davidpublishing/journals/J6/enegy2011/neng2011/547.html
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Hossain, Altab
Rahman, Mohammed Ataur
Mohiuddin, A. K. M.
Aminanda, Yulfian
Power consumption prediction for an intelligent air-cushion tracked vehicle: fuzzy expert system
description This paper describes the unique structure of an intelligent air-cushion system of a hybrid electrical air-cushion track vehicle working on swamp terrain. Fuzzy expert system (FES) is used in this study to control the swamp tracked vehicle’s intelligent air cushion system while it operates in the swamp peat. The system will be effective to control the intelligent air-cushion system with total power consumption (PC), cushion clearance height (CCH) and cushion pressure (CP). Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, pressure sensor, micro controller and battery pH sensor will be incorporated with the (FES) to investigate experimentally the PC, CCH and CP. In this study, we provide illustration how FES might play an important role in the prediction of power consumption of the vehicle’s intelligent air-cushion system. The mean relative error of actual and predicted values from the FES model on total power consumption is found as 10.63 %, which is found to be alomst equal to the acceptable limits of 10%. The goodness of fit of the prediction values from the FES model on PC is found as 0.97.
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 Power consumption prediction for an intelligent air-cushion tracked vehicle: fuzzy expert system
title_short Power consumption prediction for an intelligent air-cushion tracked vehicle: fuzzy expert system
title_full Power consumption prediction for an intelligent air-cushion tracked vehicle: fuzzy expert system
title_fullStr Power consumption prediction for an intelligent air-cushion tracked vehicle: fuzzy expert system
title_full_unstemmed Power consumption prediction for an intelligent air-cushion tracked vehicle: fuzzy expert system
title_sort power consumption prediction for an intelligent air-cushion tracked vehicle: fuzzy expert system
publisher David Publishing, USA
publishDate 2010
url http://irep.iium.edu.my/17055/
http://irep.iium.edu.my/17055/
http://irep.iium.edu.my/17055/1/Power_consumption_prediction_for_an_intelligent_air-cushion.pdf
first_indexed 2023-09-18T20:25:52Z
last_indexed 2023-09-18T20:25:52Z
_version_ 1777408412483584000

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