Design And Implementation Of The Control Method Of VAV Air-conditioning System

The role of central air conditioning system is to provide the energy of hot and cold to maintain the building a comfortable space environment. VAV system has been more widely used because of its flexibility, air quality and other characteristics. In recent years, with the developing of the air conditioning industry, its increasing energy consumption put forwards a higher demand for its energy-saving operation. Central air conditioning system is largely dependent on the control system, so the control system largely determines the parameters of the control of air conditioning, air conditioning operating efficiency and the energy efficiency. This paper focuses on intelligent control method for temperature control to maximum energy conservation, improve the speed of response.In this paper, we analyze the mechanism and working principle of VAV system, find that it’s difficult to have good effect because of the non-linear characteristics, the model uncertainty and time delay. This paper describes the principles of the ant colony optimization algorithm, modified smith predictor and fuzzy PID, and then gives a specific design for this controlled object. For VAV system, there are a variety of control options available, and in this paper, we select the ant colony optimization algorithm first. The ant colony optimization algorithm is a new bionics algorithm and it can find the optimal solution through several cycles. Second, we choose the modified smith predictor, we know that smith predictor has some shortcomings itself and after the experimental verification, we find that the modified smith predictor has better robustness and anti-jamming capability. Finally, we choose the fuzzy PID, because of its speed and feature to eliminate steady-state error, the fuzzy PID has been widely used.In the paper, we will compare the above three control methods by simulation experiments, thus choose a more suitable control strategies for VAV system.