控制系统的辨识建模及微粒群优化设计  

Identification modelling and optimum design using particle swarm optimization for control system

作　　者：郭成[1] 李群湛[1] 

机构地区：[1]西南交通大学电气工程学院成都610031

出　　处：《计算机工程与应用》2010年第15期57-59,92,共4页Computer Engineering and Applications

基　　金：国家“十一五”科技支撑计划重大项目资助No.2007BAA12B5~~

摘　　要：针对控制系统的传递函数建模与控制器的参数优化问题,提出了基于Prony和微粒群优化(PSO)算法的设计方案。首先在被控对象的输入端施加一个脉冲信号,然后对其输出信号进行Prony分析,得出该被控对象的传递函数,最后采用改进PSO算法进行控制器的参数优化设计。基于辨识的Prony算法可快速准确得出被控对象的传递函数;基于T-S模型模糊自适应的改进PSO算法(T-SPSO算法)依据种群当前最优性能指标和惯性权重自适应惯性权重取值,较好解决了PSO算法的早熟问题,可以更好地优化控制器参数。该方案实现了控制系统的精确建模与优化设计,仿真结果验证了所提方案的有效性。In order to solve the transfer function modelling and controller parameter optimization of control systems,a novel design scheme is presented based on prony and particle swarm optimization（PSO） method.In this scheme,an impulse signal is applied to the input of controlled member firstly,and then output signal is estimated by prony analysis to get the transfer function. Finally,controller parameter is optimized by the improved PSO algorithm.The transfer function of controlled member can be obtained by prony algorithm rapidly and accurately;Fuzzy adaptive PSO algorithm based on T-S model （T-SPSO）,which effectively solve the premature problem of PSO by adaptively updating the inertia weight according to the best current fitness and inertia weight,can perfectly optimize controller parameter.The presented scheme solves the accurate modeling and optimum design problem of control systems effectively,and simulation results verify the validity of the developed method.

关 键 词：传递函数 辨识 PRONY算法 微粒群算法 基于T-S模型的PSO算法(T-SPSO) 比例-积分-微分(PID)控制 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程] TP273.2[自动化与计算机技术—控制科学与工程]