AN IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM AND ITS APPLICATION IN IDENTIFICATION THROUGH THERMODYNAMIC PROCESS MODEL

GAO Wen-song; LIU Chang-liangDepartment of Automation

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AN IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM AND ITS APPLICATION IN IDENTIFICATION THROUGH THERMODYNAMIC PROCESS MODEL

更新时间：2025-09-28

- AN IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM AND ITS APPLICATION IN IDENTIFICATION THROUGH THERMODYNAMIC PROCESS MODEL
- Thermal Power Generation Vol. 39, Issue 3, Pages: 97-100(2010)
- 作者机构：
  
  华北电力大学自动化系
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP301.6
- Published：2010
- 稿件说明：
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GAO Wen-song, LIU Chang-liangDepartment of Automation. AN IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM AND ITS APPLICATION IN IDENTIFICATION THROUGH THERMODYNAMIC PROCESS MODEL[J]. Thermal power generation, 2010, 39(3): 97-100.
DOI：

GAO Wen-song, LIU Chang-liangDepartment of Automation. AN IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM AND ITS APPLICATION IN IDENTIFICATION THROUGH THERMODYNAMIC PROCESS MODEL[J]. Thermal power generation, 2010, 39(3): 97-100. DOI：

摘要

为了提高基本粒子群优化(PSO)算法的收敛性

提出了一种引入选择与变异机制的改进PSO算法。该算法选择一定范围的优秀粒子代替较差粒子

并使粒子以不同的概率变异。仿真试验表明

引入选择与变异机制使PSO算法的收敛速度得到了提高

并且有效抑制了PSO算法的早熟。将改进PSO算法应用于热工过程模型辨识

在较少的迭代次数内得到了比较精确的模型辨识结果

且具有很好的收敛性能

获得了满意的辨识效果。

Abstract

In order to enhance the convergent behavior of the basic particle swarm optimization(PSO) algorithm

an improved PSO algorithm

into which the selection and mutation mechnisms being introduced

has been put forward.In the improved algorithm

a range of excellent particles is selected to substute the poor particles

and make the particles to mutate with different probability.Emulation test shows that the introduction of selection and mutation mechnisms makes the covergent rate PSO algorithm to be enhanced

and the precocity of PSO algorithm to be effectively restrained.The improved PSO algorithm has been used in identification through thermodynamic process model

a more precise result of model identification can be achieved in a smaller number of iterations

boasting very good convergent behavior

obtaining satisfactory results in identificarion.

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