引用本文:廖迎新, 吴敏, 佘锦华, 曹卫华.基于HPSO的钢坯加热过程炉温优化设定[J].控制理论与应用,2007,24(6):1010~1014.[点击复制]
LIAO Ying-xin, WU Min, SHE Jin-hua, CAOWei-hua.Hybrid particle swarm optimization of temperature settings of billet-reheating process[J].Control Theory and Technology,2007,24(6):1010~1014.[点击复制]
基于HPSO的钢坯加热过程炉温优化设定
Hybrid particle swarm optimization of temperature settings of billet-reheating process
摘要点击 1525  全文点击 1296  投稿时间：2006-11-09  修订日期：2007-04-29
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DOI编号  10.7641/j.issn.1000-8152.2007.6.029
  2007,24(6):1010-1014
中文关键词  加热炉  稳态优化  混合粒子群优化  免疫  克隆
英文关键词  reheating furnace  steady-state optimization  hybrid particle swarm optimization  immunity  cloning
基金项目  国家杰出青年科学基金资助项目(60425310); 国家863计划项目(2006AA04Z172); 湖南省科技计划项目(04FJ3029).
作者单位
廖迎新, 吴敏, 佘锦华, 曹卫华 中南大学信息科学与工程学院, 湖南长沙410083
中南林业科技大学电子与信息工程学院, 湖南长沙410004
东京工科大学仿生学学部, 日本东京192-0982 
中文摘要
      针对一种蓄热推钢式加热炉三个加热区的炉温稳态优化问题, 本文提出了一种混合粒子群优化(HPSO)方法. 首先, 基于钢坯导热偏微分方程和边界条件, 建立钢坯温度预报模型. 然后, 采用HPSO算法确定最佳稳态炉温,即炉温控制的参考输入. 该方法利用混沌机制产生初始种群, 通过免疫和克隆来提高粒子群优化(PSO)算法的全局搜索能力和搜索精度.
英文摘要
      A hybrid particle swarm optimization (HPSO) approach is presented to solve the problem of optimizing the steady-state temperatures of the three zones of a billet reheating furnace. Firstly, a model for predicting billet temperature is constructed based on a heat transfer equation and its boundary conditions. Then, HPSO is used to determine the optimal steady-state temperatures, which are reference inputs for the control of furnace temperature. This approach uses a chaos mechanism to create the initial population, and adopts immunity and cloning to improve the global search capability and search precision of particle swarm optimization.