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Genetic algorithm identification for automotive air-conditioning system

In this study, system identification of an automotive air conditioning (AAC) system with different parameter estimation methods were conducted. The AAC experiment rig which comes complete with an air duct system to simulate the actual behaviour of AAC system was used to acquire the input and output...

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主要な著者: Md Lazin, M. N., Mat Darus, I. Z., Ng, B. C., Kamar, H. M.
フォーマット: Conference or Workshop Item
出版事項: 2013
主題:
TJ Mechanical engineering and machinery
オンライン･アクセス:http://eprints.utm.my/id/eprint/51090/
http://dx.doi.org/10.1109/ISCI.2013.6612368
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spelling my.utm.510902017-09-13T07:54:38Z http://eprints.utm.my/id/eprint/51090/ Genetic algorithm identification for automotive air-conditioning system Md Lazin, M. N. Mat Darus, I. Z. Ng, B. C. Kamar, H. M. TJ Mechanical engineering and machinery In this study, system identification of an automotive air conditioning (AAC) system with different parameter estimation methods were conducted. The AAC experiment rig which comes complete with an air duct system to simulate the actual behaviour of AAC system was used to acquire the input and output datasets for the identification of the system. The single input single output dynamic model was established by using Autoregressive with exogenous input (ARX) model. Recursive Least Square (RLS) and Genetic Algorithm (GA) were used to optimize the ARX model and hence to obtain the dynamic model of AAC system based on one-step-ahead (OSA) prediction. The performances of the models were validated using statistical analysis based on the mean squares of error (MSE) between the actual and predicted output responses of the models. The comparison results between these parameter estimation optimization techniques were highlighted. The GA optimization method produce the best ARX model with the lowest prediction MSE value of 0.0015059 and it was proposed to be used to represent the AAC system for further development of the controller strategy. 2013 Conference or Workshop Item PeerReviewed Md Lazin, M. N. and Mat Darus, I. Z. and Ng, B. C. and Kamar, H. M. (2013) Genetic algorithm identification for automotive air-conditioning system. In: IEEE Symposium on Computers and Informatics, ISCI 2013. http://dx.doi.org/10.1109/ISCI.2013.6612368
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/
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Md Lazin, M. N.
Mat Darus, I. Z.
Ng, B. C.
Kamar, H. M.
Genetic algorithm identification for automotive air-conditioning system
description In this study, system identification of an automotive air conditioning (AAC) system with different parameter estimation methods were conducted. The AAC experiment rig which comes complete with an air duct system to simulate the actual behaviour of AAC system was used to acquire the input and output datasets for the identification of the system. The single input single output dynamic model was established by using Autoregressive with exogenous input (ARX) model. Recursive Least Square (RLS) and Genetic Algorithm (GA) were used to optimize the ARX model and hence to obtain the dynamic model of AAC system based on one-step-ahead (OSA) prediction. The performances of the models were validated using statistical analysis based on the mean squares of error (MSE) between the actual and predicted output responses of the models. The comparison results between these parameter estimation optimization techniques were highlighted. The GA optimization method produce the best ARX model with the lowest prediction MSE value of 0.0015059 and it was proposed to be used to represent the AAC system for further development of the controller strategy.
format Conference or Workshop Item
author Md Lazin, M. N.
Mat Darus, I. Z.
Ng, B. C.
Kamar, H. M.
author_facet Md Lazin, M. N.
Mat Darus, I. Z.
Ng, B. C.
Kamar, H. M.
author_sort Md Lazin, M. N.
title Genetic algorithm identification for automotive air-conditioning system
title_short Genetic algorithm identification for automotive air-conditioning system
title_full Genetic algorithm identification for automotive air-conditioning system
title_fullStr Genetic algorithm identification for automotive air-conditioning system
title_full_unstemmed Genetic algorithm identification for automotive air-conditioning system
title_sort genetic algorithm identification for automotive air-conditioning system
publishDate 2013
url http://eprints.utm.my/id/eprint/51090/
http://dx.doi.org/10.1109/ISCI.2013.6612368
_version_ 1643652936097595392
score 13.251813

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