基于改进PSO的原动机仿真系统PI参数优化  

Optimizing PI Parameters in Prime Mover Simulation System Based on Improved Particle Swarm Optimization Algorithm

作　　者：曾崇群[1] 刘觉民[1] 鲁文军[1] 宋海燕[1] 

机构地区：[1]湖南大学电气与信息工程学院,长沙410082

出　　处：《电力系统及其自动化学报》2012年第1期100-103,共4页Proceedings of the CSU-EPSA

基　　金：湖南省科技计划项目(2010CK3016);湖南大学"中央高校基本科研业务费"能力培养类项目(2009y)

摘　　要：原动机仿真系统中的速度电流综合调节器实质为PI调节器,其比例系数kP和时间常数τL依靠传统方法难以确定。针对此问题,提出一种改进的粒子群优化算法,以ITAE指标作为改进PSO优化算法的适应度函数。通过具体实例,运用MATLAB仿真试验,比较分析传统方法、免疫遗传算法和改进粒子群算法的控制效果。试验结果表明:改进的PSO优化算法简单实用,并可显著提高原动机仿真系统的动态特性。In the prime mover simulation system,parameters of the PI regulator,such as ratio coefficient kP and time constantτL,are difficult to be determined by the traditional methods.To solve this problem,this paper proposed an improved PSO algorithm with the ITAE criterion of speed errors as the fitness function of the improved PSO algorithm.By using the specific example and the MATLAB simulation,the traditional method,the immune genetic algorithm and the improved particle swarm control were compared.The results showed that the improved PSO algorithm can easily and accurately find the optimal PI parameters,and significantly enhance the enable the dynamic characteristic of prime mover simulation system.

关 键 词：粒子群优化 原动机仿真 PI调节器 参数优化 

分 类 号：TM743[电气工程—电力系统及自动化]