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Dynamic indoor thermal comfort model identification based on neural computing PMV index

This paper focuses on modelling and simulation of building dynamic thermal comfort control for non-linear HVAC system. Thermal comfort in general refers to temperature and also humidity. However in reality, temperature or humidity is just one of the factors affecting the thermal comfort but not the...

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Main Authors:	Sahari K.S.M., Jalal M.F.A., Homod R.Z., Eng Y.K.
Other Authors:	57218170038
Format:	Conference paper
Published:	Institute of Physics Publishing 2023
Subjects:	Papaya mosaic virus Delay control systems Neural networks Thermal comfort Comfort sensations Indoor thermal comfort Input-output mapping Modelling and simulations Nonlinear behaviours Nonlinear mappings Thermal comfort control Thermal sensations air conditioning artificial neural network building control system heating humidity index method numerical model temperature profile ventilation Sensory perception
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id	my.uniten.dspace-30216
record_format	dspace
spelling	my.uniten.dspace-302162023-12-29T15:45:35Z Dynamic indoor thermal comfort model identification based on neural computing PMV index Sahari K.S.M. Jalal M.F.A. Homod R.Z. Eng Y.K. 57218170038 37116431100 36994633500 55812454700 Papaya mosaic virus Delay control systems Neural networks Thermal comfort Comfort sensations Indoor thermal comfort Input-output mapping Modelling and simulations Nonlinear behaviours Nonlinear mappings Thermal comfort control Thermal sensations air conditioning artificial neural network building control system heating humidity index method numerical model temperature profile ventilation Sensory perception This paper focuses on modelling and simulation of building dynamic thermal comfort control for non-linear HVAC system. Thermal comfort in general refers to temperature and also humidity. However in reality, temperature or humidity is just one of the factors affecting the thermal comfort but not the main measures. Besides, as HVAC control system has the characteristic of time delay, large inertia, and highly nonlinear behaviour, it is difficult to determine the thermal comfort sensation accurately if we use traditional Fanger's PMV index. Hence, Artificial Neural Network (ANN) has been introduced due to its ability to approximate any nonlinear mapping. Using ANN to train, we can get the input-output mapping of HVAC control system or in other word; we can propose a practical approach to identify thermal comfort of a building. Simulations were carried out to validate and verify the proposed method. Results show that the proposed ANN method can track down the desired thermal sensation for a specified condition space. � Published under licence by IOP Publishing Ltd. Final 2023-12-29T07:45:35Z 2023-12-29T07:45:35Z 2013 Conference paper 10.1088/1755-1315/16/1/012113 2-s2.0-84881101851 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84881101851&doi=10.1088%2f1755-1315%2f16%2f1%2f012113&partnerID=40&md5=9fd9c3f3944e84b2c0581da697c29ffc https://irepository.uniten.edu.my/handle/123456789/30216 16 1 12113 All Open Access; Gold Open Access Institute of Physics Publishing Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
topic	Papaya mosaic virus Delay control systems Neural networks Thermal comfort Comfort sensations Indoor thermal comfort Input-output mapping Modelling and simulations Nonlinear behaviours Nonlinear mappings Thermal comfort control Thermal sensations air conditioning artificial neural network building control system heating humidity index method numerical model temperature profile ventilation Sensory perception
spellingShingle	Papaya mosaic virus Delay control systems Neural networks Thermal comfort Comfort sensations Indoor thermal comfort Input-output mapping Modelling and simulations Nonlinear behaviours Nonlinear mappings Thermal comfort control Thermal sensations air conditioning artificial neural network building control system heating humidity index method numerical model temperature profile ventilation Sensory perception Sahari K.S.M. Jalal M.F.A. Homod R.Z. Eng Y.K. Dynamic indoor thermal comfort model identification based on neural computing PMV index
description	This paper focuses on modelling and simulation of building dynamic thermal comfort control for non-linear HVAC system. Thermal comfort in general refers to temperature and also humidity. However in reality, temperature or humidity is just one of the factors affecting the thermal comfort but not the main measures. Besides, as HVAC control system has the characteristic of time delay, large inertia, and highly nonlinear behaviour, it is difficult to determine the thermal comfort sensation accurately if we use traditional Fanger's PMV index. Hence, Artificial Neural Network (ANN) has been introduced due to its ability to approximate any nonlinear mapping. Using ANN to train, we can get the input-output mapping of HVAC control system or in other word; we can propose a practical approach to identify thermal comfort of a building. Simulations were carried out to validate and verify the proposed method. Results show that the proposed ANN method can track down the desired thermal sensation for a specified condition space. � Published under licence by IOP Publishing Ltd.
author2	57218170038
author_facet	57218170038 Sahari K.S.M. Jalal M.F.A. Homod R.Z. Eng Y.K.
format	Conference paper
author	Sahari K.S.M. Jalal M.F.A. Homod R.Z. Eng Y.K.
author_sort	Sahari K.S.M.
title	Dynamic indoor thermal comfort model identification based on neural computing PMV index
title_short	Dynamic indoor thermal comfort model identification based on neural computing PMV index
title_full	Dynamic indoor thermal comfort model identification based on neural computing PMV index
title_fullStr	Dynamic indoor thermal comfort model identification based on neural computing PMV index
title_full_unstemmed	Dynamic indoor thermal comfort model identification based on neural computing PMV index
title_sort	dynamic indoor thermal comfort model identification based on neural computing pmv index
publisher	Institute of Physics Publishing
publishDate	2023
_version_	1806425806193295360
score	13.211869

Dynamic indoor thermal comfort model identification based on neural computing PMV index

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