Performance Assessment of Multivariate Control System Based on Data-Driven Covariance Historical Benchmark

  • Hong Qian
  • Gaofeng JiangEmail author
  • Yuan Yuan
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 924)


In order to better meet the on-site monitoring requirements and ensure the control system is running well, the performance assessment for multivariate control system (MIMO) is an increasing concern. According to the generalized eigenvalue analysis, multiple performance indexes based on the eigenvalues was proposed, and big data of process output was used to obtain a history data set and establish a historical benchmark, which can not only monitor the adjustment ability of single closed-loop, but also get the change of the overall control performance. A user-definable indicator is put forward to select the historical data set, then, based on the statistical analysis theory, the benchmark is improved and multiple performance levels are divided. Finally, the performance evaluation method is presented for MIMO. An example for monitoring the performance of the coordination control system (CCS) is illustrated to show the use and effectiveness and objectivity of the proposed method.


Performance assessment Data-driven Multivariate control system Historical benchmark Statistical analysis theory Performance levels 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Shanghai University of Electric PowerShanghaiChina
  2. 2.Shanghai Power Station Automation Technology Key LaboratoryShanghaiChina

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