Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/26375
Title: A novel neural network aided fuzzy logic controller for a variable speed (VS) direct expansion (DX) air conditioning (A/C) system
Authors: Li, Z
Xu, X
Deng, S 
Pan, D
Keywords: Artificial neural network
Conditioning
Fuzzy logic
Inherent correlation
Simultaneous control
Variable speed direct expansion air
Issue Date: 2015
Publisher: Pergamon Press
Source: Applied thermal engineering, 2015, v. 78, p. 9-23 How to cite?
Journal: Applied thermal engineering 
Abstract: A novel artificial neural network (ANN) aided fuzzy logic controller for simultaneous control of indoor air temperature and humidity using a variable speed (VS) direct expansion (DX) air conditioning (A/C) system, through combining the complementary merits of fuzzy logic controllers and ANN modeling was developed and is reported in this paper. A novel control principle was proposed to decouple the temperature and humidity control loops by introducing two interim variables of sensible and latent output cooling capacity of the DX A/C system. A fuzzy logic system was redesigned to simplify both its calculation and structure by using weights of linguistic variables. To enable the ANN model developed to be functional at the normal operational range of indoor air parameters, previously reported inherent operating characteristics of a VS DX A/C system were used for training and testing the ANN models. The novel controller so developed was tested using an experimental VS DX A/C system. Both the command following tests and disturbance rejection tests showed that the air dry-bulb and wet-bulb temperatures were properly controlled by the controller developed with satisfactory control performances in terms of control accuracy and sensitivity.
URI: http://hdl.handle.net/10397/26375
ISSN: 1359-4311
EISSN: 1873-5606
DOI: 10.1016/j.applthermaleng.2014.12.030
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