Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (15): 57-59.DOI: 10.3778/j.issn.1002-8331.2010.15.018

• 研发、设计、测试 • Previous Articles     Next Articles

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

GUO Cheng,LI Qun-zhan   

  1. School of Electrical Engineering,Southwest Jiaotong University,Chengdu 610031,China
  • Received:2009-03-17 Revised:2009-05-14 Online:2010-05-21 Published:2010-05-21
  • Contact: GUO Cheng

控制系统的辨识建模及微粒群优化设计

郭 成,李群湛   

  1. 西南交通大学 电气工程学院 成都 610031
  • 通讯作者: 郭 成

Abstract: 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.

Key words: transfer function, idemtification, Prony algorithm, particle swarm optimization, PSO algorithm based on T-S model(T-SPSO), Proportion-Integral-Derivative(PID) control

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。

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

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