改进粒子群优化PID的变风量空调控制策略  

Control Method of VAV Air-Conditioning System Based on Bacterial Foraging Particle Swarm Optimization Algorithm and PID Control

作　　者：杨晨[1] 孙欢[2] 

机构地区：[1]天津商业大学网络中心,天津300400 [2]天津商业大学机械工程学院,天津300400

出　　处：《计算机仿真》2014年第6期424-428,共5页Computer Simulation

摘　　要：研究变风量空调控制问题,风量空调系统具有非线性﹑时变性,传统PID控制方法不能获得高精度的控制效果。为了提高风量空调的控制精度,提出了一种细菌觅食粒子群优化PID的变风量空调控制策略。首先利用非线性PID控制实现各参数增益的实时调整,提高抗干扰能力,然后利用细菌觅食粒子群优化算法根据系统偏差动态优化非线性PID控制器参数,以提高控制精度,在Simulink环境下对变风量空调系统进行仿真研究。仿真结果表明,改进控制策略具有鲁棒性强,控制精度高,大幅度改善了变风量空调系统的性能。In order to improve the performance of VAV air conditioning system which is nonlinear and time varying, a novel control method of VAV air - conditioning systems was proposed based on bacterial foraging particle swarm optimization algorithm and PID control. Firstly, the nonlinear PID controller adjusted the gain parameter following the changes of error, enhances anti -jamming capability, and then bacterial foraging particle swarm optimization algorithm was used in dynamic deviation to optimize the controller parameter of nonlinear PID in the speed control system to reduce the overshoots and strengthen control accuracy. Finally, the simulation experiment was carried out in Simulink environment. The simulation results show that the proposed method has good robustness, high control precision, and greatly improves the performance of VAV air conditioning system.

关 键 词：模型辨识 细菌觅食算法 粒子群优化算法 变风量空调系统 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]