粒子群优化PID在变风量空调系统中的应用  

Application of the Particle Swarm Optimization PID in VAV Air Conditioning System

作　　者：王长涛[1] 郭高超 赵剑明[2] 韩忠华[1,2,3] 朱毅[1] 

机构地区：[1]沈阳建筑大学信息与控制工程学院,辽宁沈阳110168 [2]中国科学院沈阳自动化研究所,辽宁沈阳110016 [3]中国科学院网络化控制系统重点实验室,辽宁沈阳110016

出　　处：《自动化仪表》2018年第2期7-11,16,共6页Process Automation Instrumentation

基　　金：国家高技术研究发展计划(863计划)基金资助项目(2015AA043901)

摘　　要：针对在变风量(VAV)空调系统中,传统PID控制自适应能力差、对非线性系统控制效果不佳的问题,提出了一种基于粒子群优化(PSO)算法整定PID参数的方法。通过选取被控对象模型(空调房间模型),在目标空间中寻找最优PID控制参数集,并选取被控系统的误差绝对值乘时间积分(ITAE)指标作为粒子群算法的目标函数。通过设计优化程序,得到了系统仿真图。与传统Ziegler-Nichols(Z-N)算法整定PID结果相比,系统在工况切换时超调量降低、调节时间缩短。为了避免粒子群算法陷入局部极值,对算法进行了加权。在系统中的应用效果表明,与基本PSO算法相比,加权后的PSO算法在系统工况切换时,收敛速度变慢、系统偏差量减小、调节时间缩短。经仿真分析得出,加权后的PSO算法能有效地降低PID控制器的超调量。该优化算法应用于具有多种变化特性的VAV空调系统中,提高了系统的控制性能。Aiming at the poor adaptive ability and the poor control effect on nonlinear system of traditional PID control in variable air volume（VAV） air conditioning system,a method of tuning PID parameters based on particle swarm optimization （PSO） is proposed.By selecting the controlled object model （the airconditioning room model）, the optimal PID control parameter set in the target space is found,and the integrated time absolute error（ITAE） performance index of the controlled system is selected as the target function of the PSO.Through designing the optimization program,the system simulation diagram is obtained.Compared with the traditional ZieglerNichols（Z-N） algorithm,the overshoot and the adjusting time under operation conditions switched over are reduced.In order to avoid PSO algorithm falls into the local extremum value,the algorithm is weighted.The application effects of the system show that comparing with basic PSO algorithm,the weighted PSO algorithm offers slower convergence speed,smaller system deviation and shorter adjusting time when operation conditions switched over.The simulation results show that weighted PSO algorithm can effectively reduce the overshoot of PID controller.This optimization method is applied to the VAV air conditioning system with various varying characteristics,and the control performance of the system is improved.

关 键 词：变风量 非线性系统 惯性权重 粒子群优化 适应度函数 PID控制 

分 类 号：TH-39[机械工程] TP27[自动化与计算机技术—检测技术与自动化装置]