Study on outlier robustness of minimum variance control performance assessment

• Published in: International journal of adaptive control and signal processing 2021-11, Vol.35 (11), p.2175-2193
• Main Authors: Kaczmarek, Kacper, Domański, Paweł D.
• Format: Article
• Language: English
• Subjects: control performance assessment; Data analysis; minimum variance; non‐Gaussian; outliers; Outliers (statistics); Performance assessment; Proportional integral derivative; Robust control; robust estimation; Sensitivity analysis; SISO (control systems); Variance analysis
• ISSN: 0890-6327; 1099-1115
• DOI: 10.1002/acs.3313

Summary Minimum variance (MinVar) method for control performance assessment constitutes one of the most common approaches to the control quality estimation. There are dozens of versions, enriched with numerous reported industrial implementations. MinVar methodology uses the idea of minimum variance, which has been introduced by Kalman. Therefore, it should be remembered that MinVar concept relies on the same assumptions as an idea of the minimum variance control. Among other assumptions, it is essential that the modeled disturbance is an independent random sequence. This article addresses scenarios, when loop noise exhibits non‐Gaussian properties and is characterized by outliers having fat‐tailed distribution. Sensitivity analysis of minimum variance method against such disturbances is evaluated using commonly used PID SISO control benchmarks. It is shown that MinVar method may be significantly biased in such non‐Gaussian situations, which are very frequent in the industrial reality. Reasons of the biased performance are traced and respective solutions are proposed.