基于PSO的改进的PID控制器在VAV空调系统温度控制中的应用

RESEARCH OF THE IMPROVED BP-NN PID CONTROLLER BASED ON PSO FOR THE VAV AIR-CONDITIONING SYSTEM

以变风量空调系统的温度控制作为研究对象,在现有的研究基础上,提出了粒子群优化算法改进的BP神经网络PID控制方法。应用BP神经网络进行PID参数在线整定,粒子群优化算法提高BP神经网络的学习速率和收敛性,结合三者各自的优势以提高变风量空调系统的控制性能。

Based on the existed research, we took the temperature control of AVA air-conditioning system as research object and put forward the BP neural network’s control theory of PID based on the particle swarm optimization. By applying BP neural network on the online installation of PID parameter, particle swarm optimization can improves the study speed and convergence of BP neural network. Combining all the three advantages,we improve the control performance of AVA air-conditioning system.