Identification and Prediction of Room Temperature Delay Neural Network Model for VAV Air Conditioning

doi:10.16182/j.issn1004731x.joss.17-0175

Abstract

Abstract: Aiming at the problem of mathematical description for dynamic response characteristic of indoor temperature time-delay system, the fundamental principle of neural network model identification is introduced in regulation process of variable air volume (VAV) air conditioning system. Considering the model structure of Elman neural network, this paper presents an optimal selection algorithm for layer delay coefficient in order to determine delay time between indoor temperature and regulation parameters; and a multiple-step prediction model of indoor temperature time-delay system based on Elman neural network is built. The effectiveness of the proposed method is validated through the simulation experiment.

Key words: temperature time-delay, neural network, model identification, VAV (Variable air volume)

CLC Number:

TP273

Li Xiuming, Zhang Jili, Zhao Tianyi, Chen Tingting. Identification and Prediction of Room Temperature Delay Neural Network Model for VAV Air Conditioning[J]. Journal of System Simulation, 2019, 31(5): 861-868.

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