改进PSO算法在中央空调控制系统中的应用  

Improved PSO Algorithm of Central Air-conditioning Control System

作　　者：杨晓庆[1] 左为恒[1] 李昌春[1] 

机构地区：[1]重庆大学输配电装备及系统安全与新技术国家重点实验室,重庆400030

出　　处：《计算机仿真》2011年第11期201-204,共4页Computer Simulation

摘　　要：在优化控制中央空调问题的研究中,中央空调房间温度控制系统是一个复杂的系统,针对保证室内温度控制的稳定性,同时还应节能减排,传统方法整定得到的PID参数难以保证系统温度控制始终处于优化状态和良好品质特性的缺点,提出了改进的PSO算法整定PID参数的方法,保证控制系统的优良品质。算法根据群体适应度变化的情况自适应调整权重,对种群中性能较差的粒子进行交叉选择,能充分挖掘群体本身信息,又能不断引入附加信息。在中央空调温度控制的仿真结果表明,改进的方法调节精度高,调节速度快,超调量小,使室温控制在需要的精度上,具有实际应用的可行性。The room temperature control system of central air conditioning is a complex system.The traditional PID tuning methods are difficult to ensure the temperature control of system always in optimizing state and good quality.The paper put forward the improved PSO algorithm which tuned PID parameters to ensure the quality of system.According to the changes of group fitness,this algorithm adjusted the weights self-adaptedly,and carried out cross-selection to the particle population in poor performance.The algorithm can fully exploit the information of the group itself and continue introducing additional information.The simulation results in central air-conditioning temperature control show that this method has high precision,quick regulation,and small overshoot,makes the temperature control stay in the accuracy in needed,and has feasibility.

关 键 词：变风量 粒子群优化算法 比例积分微分 遗传算法 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]