Research On Air Conditioning System Control Based On Predictive Fuzzy PID

VAV air-conditioning system is widely used because they can introduce fresh air to improve air quality.VAV air-conditioning system changes the air volume sent into the room in real time to adapt to the indoor load,at any time according to the indoor control quality to adjust the size of the fresh air to ensure comfort,while reducing energy consumption.However,there are problems such as uneven distribution of fresh air and poor control eflfect in variable VAV conditioning systems.Therefore,it is necessary to conduct in-depth research on both fresh air distribution and control strategies.This paper studies the clustering of air pollutants in the computer room based on the grey correlation method,and studies the control strategy and control scheme of the fresh air in the computer room.Aiming at the temperature control problem of VAV air conditioners in data center computer room,a predictive fuzzy PID control strategy was proposed and a simulation study was conducted.VAV air-conditioning experimental platform was built and relevant experimental research was completed.Firstly,based on the grey correlation degree method,the degree of influence of various pollutants in the computer room on the indoor air quality is analyzed,and the comprehensive correlation between the pollutants is obtained.The CO2 concentration is determined as the best control index of the on-demand ventilation control strategy.The CO2 concentration model of the room prediction was established based on the theoretical equation of full aeration.And the calculation formula of the minimum fresh air volume in the computer room was obtained by the CO2 concentration dilution equation.The MSE equation modification strategy is proposed to optimize the fresh air control and adjust the fresh air ratio according to the pollutant concentration.Second,in order to solve the problem of poor temperature control in the data center room,a predictive fuzzy PID control strategy is proposed.Through simulation,this control strategy is compared with fuzzy PID control and PID control.Under normal conditions,the estimated overshoot of fuzzy PID control decreased by 18.0%and 10.3%,respectively.Under the complex conditions,the overshoot of fuzzy PID control decreased by 26.5%and 21.3%,and the adjustment time decreased by 116.9s and 93.0s.After changing the set temperature,it is estimated that the overshoot of the fuzzy PID control is 1.8%and the adjustment time is 220.1s.After the gain of the transfer function is increased,the estimated overshoot of the fuzzy PID control is only 2.8%.The simulation results show that the estimated fuzzy PID control has better dynamic performance,stronger robustness,and better control effect.Finally,a VAV air-conditioning experiment platform was set up and a platform control system was designed.And completion of the PLC program with estimated fuzzy PID control.The experimental results show that the estimated stabilization time of fuzzy PID control is 4 min and 6 min less than that of fuzzy PID control and PID control,respectively.Compared with high-temperature interference,it is estimated that fuzzy PID control will decrease by 4.7%and 3.4%respectively.It is estimated that fuzzy PID control has better dynamic performance and adaptability than conventional control methods.