化工学报 ›› 2015, Vol. 66 ›› Issue (1): 307-315.DOI: 10.11949/j.issn.0438-1157.20141483

• 过程系统工程 • 上一篇    下一篇

基于多属性性能评估的焦炉加热燃烧过程在线优化控制方法

雷琪1, 颜慧1, 吴敏2   

  1. 1 中南大学信息科学与工程学院, 湖南 长沙 410083;
    2 中国地质大学自动化学院, 湖北 武汉 430074
  • 收稿日期:2014-10-07 修回日期:2014-10-17 出版日期:2015-01-05 发布日期:2015-01-05
  • 通讯作者: 雷琪
  • 基金资助:

    国家自然科学基金项目(61203018);国家高技术研究发展计划项目(2012AA040307);中南大学博士后基金资助项目。

An on-line optimal control method for combustion process of coke oven based on multi-attribute performance evaluation

LEI Qi1, YAN Hui1, WU Min2   

  1. 1 School of Information Science and Engineering, Central South University, Changsha 410083, Hunan, China;
    2 School of Automation, China University of Geosciences, Wuhan 430074, Hubei, China
  • Received:2014-10-07 Revised:2014-10-17 Online:2015-01-05 Published:2015-01-05
  • Supported by:

    supported by the National Natural Science Foundation of China (61203018), the National High Technology Research and Development Program of China (2012AA040307) and Central South University Postdoctoral Foundation.

摘要:

针对焦炉加热燃烧过程中控制器参数难以适应由加热煤气热值和结焦时间变化等因素引起的火道温度波动的问题, 设计了一种基于多属性性能评估的焦炉加热燃烧过程优化控制方法。首先通过分析焦炉加热燃烧过程的工艺特点及生产需求, 针对过程参数周期差异较大的特点, 提出了基于信息熵的多属性性能评估模型, 实现控制系统的在线性能评估。针对控制系统性能评估不合格的情况, 建立了以火道温度偏差、偏差变化率和调节时间为目标的多目标优化模型, 并采用差分进化算法进行求解, 通过控制器参数的在线调节, 保证焦炉火道温度的稳定。仿真结果表明该优化控制方法在加热煤气热值和结焦时间变化时能较好地抑制火道温度的波动。

关键词: 焦炉加热燃烧过程, 在线性能评估, 信息熵, 多目标优化模型

Abstract:

An on-line optimal control method based on multi-attribute performance evaluation aiming at adjusting the parameters of controllers to suppress the violent fluctuations of the flue temperature in combustion process of coke ovens is proposed, which are caused by the changes of coking time, the fluctuating calories of fuel gas and other factors. Firstly, the coke process characteristics and production demands are analyzed, and a multi-attribute performance evaluation model based on information entropy is proposed to evaluate the performance of the control system on line due to large difference in parameter periods. When the performance of the control system is unsatisfied, however, a multi-objective optimization model is established to minimize the setting time, the deviation and the deviation change of flue temperature. Then, the optimum parameters of the controller are solved by the multi-objective differential evolution algorithm. Finally, simulation results verify that this optimal control method can suppress the fluctuations of flue temperature when the calories of fuel gas and coking time are changing.

Key words: combustion process of coke oven, on-line performance evaluation, information entropy, multi-objective optimization model

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