Air Conditioning Optimization Control Method Based On Model Predictive Control And Machine Learning Algorithm

The invention of air conditioners has improved the indoor environment as well as people's quality of life.At the same time,it has also brought about huge consumption of energy and deterioration of the natural environment.Therefore,research on optimization control methods of air conditioners has always been a subject of great concern.For the optimal control of air conditioners,on the one hand,better control methods should be adopted to improve the control quality of air conditioners,and on the other hand,the comfort offered by air conditioners should be improved to meet the needs of different users.For the temperature optimization control of inverter air conditioner,this paper firstly establishes the model of inverter air conditioner temperature control system by theoretical modeling and experimental modeling based on air conditioning data acquisition.Then the model prediction control algorithm is applied to the temperature optimization control of inverter air conditioner.The matlab simulink simulation tool is used to simulate the inverter air conditioner under the conditions of summer cooling and winter heating.Under each of the two working conditions,simulation has been carried out respectively for three scenarios,namely,the standard model,model mismatch and anti-jamming.The effects of the traditional inverter air conditioner PID control algorithm are compared.The simulation results are analyzed.It is verified that the model predictive control algorithm for inverter air conditioner temperature optimization control has better control effect than the traditional inverter air conditioner PID control method.For the optimal control of air conditioning temperature comfort,this paper proposes a control method that uses machine learning algorithm combined with user habit data analysis.Firstly,the overall control scheme of the air conditioner is designed,and then training is conducted with the four machine learning regression algorithms,so as to obtain the regression model for air conditioning set temperature in the automatic mode.On the basis of the automatic mode,the user usage habit data table is established in the MySQL database in the cloud server,and the user's favorite air conditioning set temperature in a specific indoor and outdoor environment is obtained.Finally,the software implementation of the web-side is completed for this air-conditioning control scheme.The method can automatically set the air conditioning temperature that the user likes,and has certain innovation and practical value.