Recent developments in multivariable controller performance monitoring

S. Joe QIN*, Jie YU

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

101 Citations (Scopus)


In this paper, we give a critical overview of recent development in MIMO control performance monitoring. We discuss a number of MIMO control benchmarks including minimum variance, LQG, and user selected benchmarks. Performance measures are extended from variance based measures in SISO control to covariance based measures in MIMO control. Pros and cons of various benchmarks are discussed. The diagnosis of poor control performance relative to a benchmark is a major focus of the paper. We argue that in the MIMO setting, the worst performance directions should be analyzed from data to yield meaningful diagnosis information. Therefore, multivariate statistics should be applied for the diagnosis of the worst performance directions, rather than one loop at a time, much like its use in multivariate process monitoring. © 2006 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)221-227
Number of pages7
JournalJournal of Process Control
Issue number3
Early online date5 Jan 2007
Publication statusPublished - Mar 2007
Externally publishedYes

Bibliographical note

Supported by the Texas–Wisconsin Modeling and Control Consortium.


  • Covariance based monitoring
  • MIMO control performance monitoring
  • Minimum variance
  • Model predictive control
  • Worst performance directions


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