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Does Control Quality Matter?

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Control Performance Assessment: Theoretical Analyses and Industrial Practice

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 245))

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Abstract

This chapter initiates the book narration. It formulates the rationale for the Control Performance Assessment (CPA). Process improvement is the main raison d’être for control systems. The relationship is straightforward. Better control causes higher performance. Despite this clear relation and common understanding of the fact, the majority of the industrial loops is neither well tuned nor properly designed. Control engineers require tools and indexes that would measure how good the control system is. Moreover they require suggestions for what should be done to improve existing poor situation. The CPA research history started in 1960s and continues till nowadays. The research is ongoing. Its importance did not decrease. During fifty years of the interest several different approaches have been investigated, like data driven or model-based approaches defined using different domains. Simultaneously, as new control strategies have emerged, according assessment approaches have developed as well. Almost each control strategy, starting from SISO PID loops up to advanced control predictive and adaptive algorithms, has been addressed in the research and specific methodologies have been proposed. It has to be noted that CPA task has been initiated by industry, is being done for industry and is perpetually validated by industry. Practical aspects, especially derived from the process industry are addressed and constitutes an important aspect of this chapter and the whole book.

L’essentiel est invisible pour les yeux.

– Antoine de Saint-Exupéry

Don’t tell people how to do things, tell them what to do and let them surprise you with their results.

– George S. Patton Jr.

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    Paweł D. Domański

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Domański, P.D. (2020). Does Control Quality Matter?. In: Control Performance Assessment: Theoretical Analyses and Industrial Practice. Studies in Systems, Decision and Control, vol 245. Springer, Cham. https://doi.org/10.1007/978-3-030-23593-2_1

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