An Optimal Control for Differential Pressure of Chilled Water in Air Conditioning System

摘要

Chilled water differential pressure of a central air conditioning system is a time-varying nonlinear complex system. It is difficult to achieve good control quality by using conventional PID control loop. To control the differential pressure control loop steadily and effectively, an optimal control method of differential pressure is proposed. The particle swarm optimization (PSO) algorithm and neural network are used to adjust the PID parameters. Adjusting the frequency of the frozen pump, the differential pressure is controlled near the set value. The simulation results show that the control quality can be improved and the control precision can be improved by using the control strategy, which not only meets the requirements of control but also has strong robustness.