Performance Assessment of Control Loops

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies. . . , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for widerand rapid dissemination. Benchmarking is a technique first applied by Rank Xerox in the late 1970s for business processes. As a subject in the commercial arena, benchmarking thrives with, for example, a European Benchmarking Forum. It has taken rather longer for benchmarking to make the transfer to the technical domain and even now the subject is making a slow headway. Akey research step in this direction was taken by Harris (1989) who used minimum variance control as a benchmark for controller loop assessment. This contribution opened up the area and a significant specialist literature has now developed. Significant support for the methodologywas given by Honeywell who have controller assessment routines in their process control applications software; therefore, it is timely to welcome a (first) monograph on controller performance assessment by Biao Huang and Sirish Shah to the Advances in Industrial Control series.

A new area which is attracting much attention from process control and industrial engineers These techniques have already been evaluated with much success in industry This state-of-the-art research material has recently been published in peer-reviewed international journals and is also available as software for industry

Klappentext

The design of advanced control algorithms has largely preoccupied control practitioners' efforts. The rationale has been that systems which are difficult to control need advanced optimal, non-linear, adaptive or similar control algorithms for better regulation. Although there are a variety of advanced control design techniques, few techniques exist for computing objective measures of control loop performance from routine operating industrial process data. The purpose of this book is to show the reader the most recent techniques for univariate and multivariate controller performance assessment. Specifically, this text ponders questions such as the following:

Is your controller healthy?

Is it doing its job well?

How can one obtain a non-invasive or a model-free assessment of controller performance from routing closed-loop data?

The theoretical results are supported by simulation, experimental (in-laboratory) and industrial evaluations.

Zusammenfassung

From the reviews:

This well-written book does an excellent job of presenting the efforts of several workers ina thorough and unified manner. Many references to previous work are given. Perhaps the major new contributions presented are in the extension of single-loop techniques to the multivariable case. The authors are not afraid to consider a "typical" plant as having "hundreds and even thousands of control loops".

...if your interest lies in research or teaching in this area, this book should be on your shelf.

Measurement and Control 33 (2000) 283 (Reviewer: Ken Dutton)

Inhalt

1. Introduction.- 2. Feedback Controller Performance Assessment of Univariate Processes.- 3. Multivariate Processes: Preliminaries.- 4. Unitary Interact or Matrices and Minimum Variance Contro.- 5. Estimation of the Unitary Interactor Matrices.- 6. Feedback Controller Performance Assessment: Simple Interactor.- 7. Feedback Controller Performance Assessment: Diagonal Interactor.- 8. Feedback Controller Performance Assessment: General Interactor.- 9. Feedforward & Feedback Controller Performance Assessment.- 10. Performance Assessment of Nonminimum Phase Systems.- 11. A Unified Approach to Performance Assessment.- 12. Performance Assessment: User-specified Benchmark.- 13. Performance Assessment: LQG Benchmark.- 14. Control Loop Performance Monitoring via Model Validation.- 15. Closed-loop Identification.- 16. Practical Considerations and Industrial Case Studies.- Appendices.- References.