Application of T-S fuzzy controllers on an HVAC system

This paper focuses on designing fuzzy controllers for a kind of Heating, Ventilation, and Air Conditioning (HVAC) systems. A kind of fuzzy method based on T-S fuzzy models with nonlinear local feedbacks is applied to a specific HVAC system. Firstly, an augmented HVAC system model is got based on an...

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Main Authors:	Teng, Long, Wang, Youyi, Chen, Can, Cai, Wenjian, Li, Hua
Other Authors:	School of Electrical and Electronic Engineering
Format:	Conference or Workshop Item
Language:	English
Published:	2020
Subjects:	Engineering::Electrical and electronic engineering Fuzzy Control T-S Fuzzy Models
Online Access:	https://hdl.handle.net/10356/145033
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-145033
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spelling	sg-ntu-dr.10356-1450332020-12-12T20:11:15Z Application of T-S fuzzy controllers on an HVAC system Teng, Long Wang, Youyi Chen, Can Cai, Wenjian Li, Hua School of Electrical and Electronic Engineering School of Mechanical and Aerospace Engineering 2014 7th International Conference on Information and Automation for Sustainability Energy Research Institute @NTU Engineering::Electrical and electronic engineering Fuzzy Control T-S Fuzzy Models This paper focuses on designing fuzzy controllers for a kind of Heating, Ventilation, and Air Conditioning (HVAC) systems. A kind of fuzzy method based on T-S fuzzy models with nonlinear local feedbacks is applied to a specific HVAC system. Firstly, an augmented HVAC system model is got based on an existing model. Then control with T-S fuzzy systems with nonlinear local models is reviewed. The control gain is got by solving a set of linear matrix inequalities (LMIs) where H ∞ performance is considered. Finally, simulations and comparisons are executed to illustrate the effectiveness of this kind of fuzzy methods. National Research Foundation (NRF) Accepted version This research is funded by the Republic of Singapore’s National Research Foundation through a grant to the Berkeley Education Alliance for Research in Singapore (BEARS) for the Singapore-Berkeley Building Efficiency and Sustainability in the Tropics (SinBerBEST) Program. BEARS has been established by the University of California, Berkeley as a center for intellectual excellence in research and education in Singapore. 2020-12-09T04:19:49Z 2020-12-09T04:19:49Z 2015 Conference Paper Long, T., Wang, Y., Chen, C., Cai, W., & Li, H. (2014). Application of T-S fuzzy controllers on an HVAC system. Proceedings of 2014 7th International Conference on Information and Automation for Sustainability, 7069545-. doi:10.1109/ICIAFS.2014.7069545 978-1-4799-4598-6 https://hdl.handle.net/10356/145033 10.1109/ICIAFS.2014.7069545 en © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/ICIAFS.2014.7069545 application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Engineering::Electrical and electronic engineering Fuzzy Control T-S Fuzzy Models
spellingShingle	Engineering::Electrical and electronic engineering Fuzzy Control T-S Fuzzy Models Teng, Long Wang, Youyi Chen, Can Cai, Wenjian Li, Hua Application of T-S fuzzy controllers on an HVAC system
description	This paper focuses on designing fuzzy controllers for a kind of Heating, Ventilation, and Air Conditioning (HVAC) systems. A kind of fuzzy method based on T-S fuzzy models with nonlinear local feedbacks is applied to a specific HVAC system. Firstly, an augmented HVAC system model is got based on an existing model. Then control with T-S fuzzy systems with nonlinear local models is reviewed. The control gain is got by solving a set of linear matrix inequalities (LMIs) where H ∞ performance is considered. Finally, simulations and comparisons are executed to illustrate the effectiveness of this kind of fuzzy methods.
author2	School of Electrical and Electronic Engineering
author_facet	School of Electrical and Electronic Engineering Teng, Long Wang, Youyi Chen, Can Cai, Wenjian Li, Hua
format	Conference or Workshop Item
author	Teng, Long Wang, Youyi Chen, Can Cai, Wenjian Li, Hua
author_sort	Teng, Long
title	Application of T-S fuzzy controllers on an HVAC system
title_short	Application of T-S fuzzy controllers on an HVAC system
title_full	Application of T-S fuzzy controllers on an HVAC system
title_fullStr	Application of T-S fuzzy controllers on an HVAC system
title_full_unstemmed	Application of T-S fuzzy controllers on an HVAC system
title_sort	application of t-s fuzzy controllers on an hvac system
publishDate	2020
url	https://hdl.handle.net/10356/145033
_version_	1686109397449703424

Application of T-S fuzzy controllers on an HVAC system

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