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Robust model predictive control: A survey

  • Part II Robust Control
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Robustness in identification and control

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 245))

Abstract

This paper gives an overview of robustness in Model Predictive Control (MPC). After reviewing the basic concepts of MPC, we survey the uncertainty descriptions considered in the MPC literature, and the techniques proposed for robust constraint handling, stability, and performance. The key concept of “closedloop prediction” is discussed at length. The paper concludes with some comments on future research directions.

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Authors and Affiliations

  1. Automatic Control Laboratory, Swiss Federal Institute of Technology (ETH), Physikstrasse 3, CH-8092, Zürich, Switzerland

    Alberto Bemporad & Manfred Morari

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  1. Alberto Bemporad
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  2. Manfred Morari
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A. Garulli (Assistant Professor)A. Tesi (Assistant Professor)

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Bemporad, A., Morari, M. (1999). Robust model predictive control: A survey. In: Garulli, A., Tesi, A. (eds) Robustness in identification and control. Lecture Notes in Control and Information Sciences, vol 245. Springer, London. https://doi.org/10.1007/BFb0109870

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  • DOI: https://doi.org/10.1007/BFb0109870

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  • Print ISBN: 978-1-85233-179-5

  • Online ISBN: 978-1-84628-538-7

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