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Encyclopedia of Systems and Control pp 1–11Cite as

Linear Matrix Inequality Techniques in Optimal Control

Abstract

LMI (linear matrix inequality) techniques offer more flexibility in the design of dynamic linear systems than techniques that minimize a scalar functional for optimization. For linear state space models, multiple goals (performance bounds) can be characterized in terms of LMIs, and these can serve as the basis for controller optimization via finite-dimensional convex feasibility problems. LMI formulations of various standard control problems are described in this article, including dynamic feedback stabilization, covariance control, LQR, H ∞ control, L ∞ control, and information architecture design.

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Authors and Affiliations

  1. University of California, 92093-0411, San Diego, USA

    Robert E Skelton

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  1. Robert E Skelton
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Correspondence to Robert E Skelton .

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Editors and Affiliations

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

    John Baillieul

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

    Tariq Samad

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© 2014 Springer-Verlag London

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Skelton, R.E. (2014). Linear Matrix Inequality Techniques in Optimal Control. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_207-1

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  • DOI: https://doi.org/10.1007/978-1-4471-5102-9_207-1

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  • Online ISBN: 978-1-4471-5102-9

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Chapter history

  1. Latest

    Linear Matrix Inequality Techniques in Optimal Control
    Published:
    16 October 2019

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_207-2

  2. Original

    Linear Matrix Inequality Techniques in Optimal Control
    Published:
    03 March 2014

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_207-1

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