Research on Temperature Control System of Central Air-conditioning based on Artificial Neural Network

摘要

the results of the thermal environment shows that the human thermal comfort in the environment is composed of the thermal environment parameters (such as the temperature, humidity, wind speed and mean radiant temperature, etc.) The results of the combined effects are on the human body. The effect can be integrated by Professor Hanger's PMV (The Average Forecast votes of Predicted Mean Vote) indicators to measure. This paper has established the PMV index based on BP neural network model, and then takes this model to PMV value of input constructed by the artificial neural system can achieve direct control of PMV index method, which can dynamically adjust the indoor temperature in real time and wind speed. The simulation results can be seen to meet the thermal comfort of the premise. It is not only for the role of air-conditioning system control in a timely manner, but it can also control the comfort range for PMV index.