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Identification for PID Control

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PID Control in the Third Millennium

Part of the book series: Advances in Industrial Control ((AIC))

Abstract

In this study, we address issues arising in system identification-based plant modeling for the purpose of tuning PID controllers. We discuss some of the more celebrated tuning methods and make an attempt to anticipate future directions of identification procedures in the effort to provide reliable answers to more involved problems. The algorithmic progression of the different methods starts with easy-to-estimate, minimal information about the plant, in the form of a single frequency point in the Nyquist plot or a couple of parameters of the step response, aiming to produce the tuning parameters with back-of-the-envelope calculations. High order general models from either first-principles modeling or system identification were then used in a variety of off-line or on-line optimization problems to produce optimal PID tunings, and were often converted to the always elusive set of quick calculations that could tune a PID controller in the field. Highest in complexity, are the most recent methods which involve maximal information about the plant, in the form of one or more nominal models and a description of uncertainty, and aim for a tuning that combines high performance, adequate robustness, and high reliability. The latter appears to be the key qualitative difference between early and late identification and controller tuning procedures, that is, the ability to provide a reliable tuning with minimal trial-and-error. An alternative implementation of the same concepts can be performed as a direct optimization of the PID parameters, that can be readily converted to an attractive on-line tuning application. Finally, employing more complex, min–max identification methods can safeguard against performance deterioration problems due to disturbances or poorly designed excitation, albeit with a significant increase in computational load and identification time.

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Notes

  1. 1.

    . If F is stable, .

  2. 2.

    The Sensitivity crossover is related to the closed-loop crossover (Complementary Sensitivity) but it is better behaved in cases of right half-plane zeros near the desired bandwidth.

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Authors and Affiliations

  1. School of Electrical Computer and Energy Engineering, Arizona State University, Tempe, AZ, 85287-5706, USA

    Kostas S. Tsakalis

  2. Honeywell Technology Center, 3660 Technology Drive, Minneapolis, MN, 55418, USA

    Sachi Dash

Authors
  1. Kostas S. Tsakalis
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  2. Sachi Dash
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Correspondence to Kostas S. Tsakalis .

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Editors and Affiliations

  1. Dept of Telecommunic. & Systems Engin., School of Engineering, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, 08193, Spain

    Ramon Vilanova

  2. Facoltà di Ingegneria, Dipto. Elettronica per l'Automazione, Università Brescia, Via Branze 38, Brescia, 25123, Italy

    Antonio Visioli

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Tsakalis, K.S., Dash, S. (2012). Identification for PID Control. In: Vilanova, R., Visioli, A. (eds) PID Control in the Third Millennium. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-2425-2_10

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  • DOI: https://doi.org/10.1007/978-1-4471-2425-2_10

  • Publisher Name: Springer, London

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  • Online ISBN: 978-1-4471-2425-2

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