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历秀明


Gender:Male
Degree:Doctoral Degree
School/Department:控制科学与工程学院
Discipline:Heat and Gas Supply, Ventilation and Air Conditioning Engineering
Business Address:大连理工大学土木综合实验3号楼601
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Current position: Home >> Scientific Research >> Paper Publications
Predication control for indoor temperature time-delay using Elman neural network in variable air volume system

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Indexed by:Journal Article

Date of Publication:2017-11-01

Journal:ENERGY AND BUILDINGS

Included Journals:EI、SCIE、Scopus

Volume:154

Page Number:545-552

ISSN:0378-7788

Key Words:Prediction control; VAV terminal; Temperature time-delay; Elmanneural network

Abstract:Aiming at the prediction control for indoor temperature time-delay in variable air volume (VAV) air conditioning system, this paper presents an indoor temperature prediction control method based on Elman neural network multi-step prediction model. Firstly, this paper introduces basic control principles of pressure-dependent and pressure-independent VAV terminal through comparable analysis and points out significance of indoor temperature prediction control based on pressure-dependent VAV terminal. Then, Elman neural network multi-step prediction model and corresponding indoor temperature prediction control method for pressure-dependent VAV terminal are proposed based on the fundamental principle of periodic prediction control for time-delay system. Finally, the effect of proposed prediction control method is validated by the experimental study according to the test data of supply air volume regulating process, provided that the supply air volume control loop adopts constant static pressure control method. Experimental results indicate the proposed indoor temperature prediction control method based on pressure-dependent VAV terminal could change the conventional regulating mode of the VAV air conditioning system, which will be benefit for improving the control stability of indoor temperature control loop and other corresponding control loops. (C) 2017 Published by Elsevier B.V.