Chaos swarm optimization algorithm based thermal system identification for thermal power units
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Chaos swarm optimization algorithm based thermal system identification for thermal power units
Thermal Power GenerationVol. 43, Issue 10, Pages: 35-39(2014)
作者机构:
华北电力大学河北省发电过程仿真与优化控制工程技术研究中心
作者简介:
基金信息:
DOI:
CLC:TM621
Published:2014
稿件说明:
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WEI Genyuan, ZHAO Pengxu, HAN Pu. Chaos swarm optimization algorithm based thermal system identification for thermal power units[J]. Thermal power generation, 2014, 43(10): 35-39.
DOI:
WEI Genyuan, ZHAO Pengxu, HAN Pu. Chaos swarm optimization algorithm based thermal system identification for thermal power units[J]. Thermal power generation, 2014, 43(10): 35-39.DOI:
Chaos swarm optimization algorithm based thermal system identification for thermal power units
摘要
针对火电厂热工过程的特点及其辨识方法的不足
以及粒子群(PSO)算法易早熟
且无法得到全局最优的问题
将粒子群早熟判断机制和混沌搜索序列添加到PSO算法中构成混沌粒子群优化(CPSO)算法
提出了基于CPSO算法的热工过程辨识方法
并将该方法应用于基于现场实测数据的热工过程模型辨识中。结果表明
该方法能够使粒子群快速摆脱局部极小值
提高了算法的收敛速度和收敛精度
取得了较好的辨识效果。
Abstract
On the basis of the characteristics of thermal process
deficiency of existing methods for thermal object identification
and the weakness of particle swarm optimization(PSO)algorithm(easy to be premature and can not obtain global optimal solution)
an identification method for thermal object based on chaos particle swarm optimization(CPSO)algorithm has been proposed
by adding the particle swarm premature judgment mechanism and the chaotic search sequence into the PSO algorithm.Furthermore
this method was applied to model identification for actual measured data based thermal process.The results show this method has the ability to jump out of local minimum