化工学报 ›› 2014, Vol. 65 ›› Issue (11): 4477-4483.DOI: 10.3969/j.issn.0438-1157.2014.11.037

• 过程系统工程 • 上一篇    下一篇

基于加权L2-Hausdorff子空间距离的MPC控制回路性能诊断

尚林源, 田学民   

  1. 中国石油大学(华东)信息与控制工程学院, 山东 青岛 266580
  • 收稿日期:2014-07-16 修回日期:2014-07-26 出版日期:2014-11-05 发布日期:2014-11-05
  • 通讯作者: 田学民
  • 基金资助:

    国家自然科学基金项目(61273160,61403418);山东省优秀中青年科学家科研奖励基金项目(BS201ZZ011);中央高校基本科研业务费专项基金项目(R1405010A).

Performance diagnosis of MPC control loop based on weighted L2-Hausdorff subspace distance

SHANG Linyuan, TIAN Xuemin   

  1. School of Information and Control Engineering, China University of Petroleum, Qingdao 266580, Shandong, China
  • Received:2014-07-16 Revised:2014-07-26 Online:2014-11-05 Published:2014-11-05
  • Supported by:

    supported by the National Natural Science Foundation of China (61273160,61403418).

摘要: 针对当前MPC控制回路性能评价方法无法准确定位性能下降源的问题,提出一种基于加权L2-Hausdorff子空间距离的控制回路性能诊断方法.该方法引用恶化性能子空间表征各个性能恶化工况下的回路特征,通过基于模型预测残差的闭环潜能指标实时监测控制回路性能.当发现性能下降时,构造加权L2-Hausdorff子空间距离来度量当前回路性能模式与已知性能模式的相似度,通过距离聚类来定位回路性能下降的恶化源.最后,通过连续搅拌加热器(continuous stirred tank heater, CSTH)上的仿真实验,验证了所提方法的有效性及可靠性.

关键词: 模型预测控制, 性能诊断, 模型预测残差, 协方差, 加权子空间距离

Abstract: In the view of the problem that the current performance evaluation method of MPC control loop cannot accurately locate the source causing performance degradation. A performance diagnosis method for control loop is proposed based on weighted L2-Hausdorff subspace distance. The method characterizes the loop performance features under different poor operating conditions by using deteriorating performance subspace, and monitors the control loop performance in real time through the model prediction residual based closed-loop potential index. When the performance degradation is detected, weighted L2-Hausdorff subspace distance is constructed to measure the similarity between the current loop performance pattern and the known ones, and the source causing performance degradation is then positioned by distance clustering. Finally, the simulation experiment on the continuous stirred tank heater(CSTH) validates the effectiveness and reliability of the proposed method.

Key words: model predictive control, performance diagnosis, model prediction residual, covariance, weighted subspace distance

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