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Optimal Control via Factorization and Model Matching

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Encyclopedia of Systems and Control

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Abstract

One approach to linear control system design involves the matching of input-output models with respect to a quantification of performance. The approach is based on a parametrization of all stabilizing feedback controllers for the given plant model. This parametrization, constructed from coprime factorizations of the plant, and spectral factorization methods for solving model-matching problems, are described in this article. Both impulse-response energy and worst-case energy-gain measures of controller performance are considered.

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Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC, Australia

    Michael Cantoni

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  1. Michael Cantoni
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Correspondence to Michael Cantoni .

Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering, Boston University, Boston, MA, USA

    John Baillieul

  2. Automation and Control Solutions, Honeywell, Golden Valley, MN, USA

    Tariq Samad

Section Editor information

  1. Department of Electrical & Electronic Engineering, The University of Melbourne, Parkville, VIC, Australia

    Michael Cantoni

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Cantoni, M. (2020). Optimal Control via Factorization and Model Matching. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_206-2

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  • DOI: https://doi.org/10.1007/978-1-4471-5102-9_206-2

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5102-9

  • Online ISBN: 978-1-4471-5102-9

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

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Chapter history

  1. Latest

    Optimal Control via Factorization and Model Matching
    Published:
    07 November 2019

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_206-2

  2. Original

    Optimal Control via Factorization and Model Matching
    Published:
    02 October 2014

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_206-1

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