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Robust Stability and Performance Analysis of Uncertain Systems Using Linear Matrix Inequalities

Author

Listed:
  • V. Balakrishnan

    (Purdue University)

  • R. L. Kashyap

    (Purdue University)

Abstract

A wide variety of problems in system and control theory can be formulated or reformulated as convex optimization problems involving linear matrix inequalities (LMIs), that is, constraints requiring an affine combination of symmetric matrices to be positive semidefinite. For a few very special cases, there are analytical solutions to these problems, but in general LMI problems can be solved numerically in a very efficient way. Thus, the reduction of a control problem to an optimization problem based on LMIs constitutes, in a sense, a solution to the original problem. The objective of this article is to provide a tutorial on the application of optimization based on LMIs to robust control problems. In the first part of the article, we provide a brief introduction to optimization based on LMIs. In the second part, we describe a specific example, that of the robust stability and performance analysis of uncertain systems, using LMI optimization.

Suggested Citation

  • V. Balakrishnan & R. L. Kashyap, 1999. "Robust Stability and Performance Analysis of Uncertain Systems Using Linear Matrix Inequalities," Journal of Optimization Theory and Applications, Springer, vol. 100(3), pages 457-478, March.
    • Handle: RePEc:spr:joptap:v:100:y:1999:i:3:d:10.1023_a:1022626120665
    DOI: 10.1023/A:1022626120665
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    References listed on IDEAS

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    1. Robert G. Bland & Donald Goldfarb & Michael J. Todd, 1981. "Feature Article—The Ellipsoid Method: A Survey," Operations Research, INFORMS, vol. 29(6), pages 1039-1091, December.
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