Encyclopedia of Systems and Control

Living Edition
| Editors: John Baillieul, Tariq Samad

Controller Performance Monitoring

  • Sirish L. ShahEmail author
Living reference work entry

Latest version View entry history

DOI: https://doi.org/10.1007/978-1-4471-5102-9_246-2


Process control performance is a cornerstone of operational excellence in a broad spectrum of industries such as refining, petrochemicals, pulp and paper, mineral processing, power systems, and wastewater treatment. Control performance assessment and monitoring applications have become mainstream in these industries and are changing the maintenance methodology surrounding control assets from predictive to condition based. The large numbers of these assets on most sites compared to the number of maintenance and control personnel have made monitoring and diagnosing control problems challenging. For this reason, automated controller performance monitoring technologies have been readily embraced by these industries.

This entry discusses the theory as well as practical application of controller performance monitoring tools as a requisite for monitoring and maintaining basic as well as advanced process control (APC) assets in the process industry. The section begins with the introduction to the theory of performance assessment as a technique for assessing the performance of the basic control loops in a plant. Performance assessment allows detection of performance degradation in the basic control loops in a plant by monitoring the variance in the process variable and comparing it to that of a minimum variance controller. Other metrics of controller performance are also reviewed. The resulting indices of performance give an indication of the level of performance of the controller and an indication of the action required to improve its performance; the diagnosis of poor performance may lead one to look at remediation alternatives such as retuning controller parameters or process reengineering to reduce delays or implementation of feed-forward control or attribute poor performance to faulty actuators or other process nonlinearities.


Time series analysis; Minimum variance control; Control loop performance assessment; Performance monitoring; Fault detection and diagnosis 
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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2020

Authors and Affiliations

  1. 1.Department of Chemical and Materials EngineeringUniversity of Alberta EdmontonEdmontonCanada

Section editors and affiliations

  • Sebastian Engell
    • 1
  1. 1.Fakultät Bio- und ChemieingenieurwesenTechnische Universität DortmundDortmundGermany