基于协方差指标预测的MPC实时性能监控

田学民; 史亚杰; 曹玉苹

doi:10.3724/SP.J.1004.2013.00658

基于协方差指标预测的MPC实时性能监控

doi: 10.3724/SP.J.1004.2013.00658

1.
中国石油大学(华东)信息与控制工程学院青岛 266580

详细信息

通讯作者:
田学民

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- 被引次数: 0
出版历程
- 收稿日期: 2012-05-15
- 修回日期: 2012-11-29
- 刊出日期: 2013-05-20

Real-time Performance Monitoring of MPC Based on Covariance Index Prediction

1.
College of Information and Control Engineering, China University of Petroleum, Qingdao 266580

摘要

摘要: 为利用过程数据实时监控模型预测控制(Model predictive control, MPC)的性能, 提出一种基于协方差预测残差的性能监控方法.首先在分析模型预测控制器优化函数和控制结构的基础上, 构造包含预测误差、控制量和过程输出的监控变量集, 然后利用滑动时间窗口建立基于协方差的实时性能评价指标.针对协方差指标缺少控制限的问题, 建立实时协方差指标的时间序列模型, 根据协方差指标的预测残差检测模型预测控制性能下降.进一步利用基于数据集相似度的性能诊断方法确定性能恶化源.最后通过Wood-Berry二元精馏塔上的仿真研究验证了所提方法的有效性.
- 性能监控 /
- 模型预测控制 /
- 协方差 /
- 预测残差 /
- 相似度
Abstract: Aiming at monitoring model predictive control performance real-timely by using process data, a covariance prediction error based performance monitoring method is proposed. On the basis of analyzing MPC optimal objective and control structure, a monitored variable set composed of prediction errors, manipulated variables and process output variables is developed. Then, a covariance based real-time performance assessment index is presented by adopting a moving window. For the problem that covariance index has no control limits, a time sequence model for real-time covariance index is presented. The predictive residual of covariance index is monitored to detect MPC performance deterioration. The source of performance deterioration can be located by using a performance diagnosis method based on data set similarity. Simulations on the Wood-Berry binary distillation column demonstrate the effectiveness of the foregoing scheme.
- Performance monitoring /
- model predictive control (MPC) /
- covariance /
- predictive residual /
- similarity

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参考文献(1)

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