| 一种改进粒子群算法及其在热工过程模型辨识中的应用 |
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| 引用本文： | 高文松,刘长良.一种改进粒子群算法及其在热工过程模型辨识中的应用[J].热力发电,2010,39(3). |
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| 作者姓名： | 高文松 刘长良 |
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| 作者单位： | 华北电力大学自动化系,河北,保定,071000 |
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| 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。
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| 关 键 词： | PSO算法 选择与变异 热工过程 模型辨识 收敛性 |
AN IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM AND ITS APPLICATION IN IDENTIFICATION THROUGH THERMODYNAMIC PROCESS MODEL |
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| GAO Wen-song,LIU Chang-liang.AN IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM AND ITS APPLICATION IN IDENTIFICATION THROUGH THERMODYNAMIC PROCESS MODEL[J].Thermal Power Generation,2010,39(3). |
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| Authors: | GAO Wen-song LIU Chang-liang |
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| Affiliation: | GAO Wen-song,LIU Chang-liangDepartment of Automation,North China Electric Power University,Baoding 071000,Hebei,Province,PRC |
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| 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... |
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| Keywords: | PSO algorithm selection and mutation thermodynamic process model identification |
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