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Contractive Model Predictive Control with Local Linearization for Nonlinear Systems

  • Chapter
Nonlinear Model Based Process Control

Part of the book series: NATO ASI Series ((NSSE,volume 353))

Abstract

Most model predictive control (MPC) schemes in the literature designed for constrained nonlinear systems involve the solution of nonlinear programming problems (NLPs). Due to the difficulties inherent to solving NLPs and since MPC requires the optimal (feasible) solution to be computed on-line and at each time step, it is important to simplify the controller from a computational point of view. Furthermore, many nonlinear MPC controllers do not provide any stability or performance guarantees for the closed-loop system. In this paper we propose a stabilizing MPC controller which can be implemented as a quadratic programming (QP) problem. Because we use local linear approximations of the nonlinear plant for prediction and because stability is guaranteed through the introduction of an additional state constraint in the optimization called contractive constraint, this scheme has been denoted contractive MPC with local linearization.

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Author information

Authors and Affiliations

  1. California Institute of Technology, Pasadena, California, 91125, USA

    Simone Loureiro de Oliveira

  2. Automatic Control Laboratory, ETH-Zentrum, 8092, Zürich, Switzerland

    Manfred Morari

Authors
  1. Simone Loureiro de Oliveira
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  2. Manfred Morari
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Editor information

Editors and Affiliations

  1. Department of Chemical Engineering, Ankara University, Tandoğan, Ankara, Turkey

    Ridvan Berber

  2. Department of Chemical Engineering, The University of Michigan, Ann Arbor, Michigan, USA

    Costas Kravaris

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© 1998 Springer Science+Business Media Dordrecht

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de Oliveira, S.L., Morari, M. (1998). Contractive Model Predictive Control with Local Linearization for Nonlinear Systems. In: Berber, R., Kravaris, C. (eds) Nonlinear Model Based Process Control. NATO ASI Series, vol 353. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-5094-1_14

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  • DOI: https://doi.org/10.1007/978-94-011-5094-1_14

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-6140-7

  • Online ISBN: 978-94-011-5094-1

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