The conceptual model of neuro-fuzzy regulation of the microclimate in the room

The purpose of this study is to develop a model of neuro-fuzzy regulation of the microclimate in the room. The proposed model consists of an artificial neural network serving to form a comfort index PMV, a fuzzy logic controller for regulating temperature and humidity in the room. The fuzzy controller takes three in-put values - the current temperature and humidity, the value of the PMV index. The fuzzy controller regulates the level of heating/cooling and dehumidification/humidification of room air. This approach makes it easy to manage these parameters through an estimate of the PMV index, which indicates the level of thermal comfort in the room. The humidity level serves to adjust the comfort index, which in some cases avoids temperature adjustments. If the PMV index obtained on the basis of the actual temperature and humidity parameters is outside optimal values, the fuzzy controller, based on the developed rule base, begins to generate a control signal for the climate control device in order to achieve the optimum level of thermal comfort. The model is developed using Matlab software. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.