Robust pole placement in LMI regions

Discusses analysis and synthesis techniques for robust pole placement in linear matrix inequality (LMI) regions, a class of convex regions of the complex plane that embraces most practically useful stability regions. The focus is on linear systems with static uncertainty on the state matrix. For thi...

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Bibliographic Details
Published in:IEEE transactions on automatic control 1999-12, Vol.44 (12), p.2257-2270
Main Authors: Chilali, M., Gahinet, P., Apkarian, P.
Format: Article
Language:English
Subjects:
Clustering
Linear matrix inequalities
Linear systems
Mathematical models
Pole placement
Poles
Robust control
Robust stability
Robustness
Stability
Stability analysis
State feedback
Synthesis
System testing
Uncertain systems
Uncertainty
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Summary:Discusses analysis and synthesis techniques for robust pole placement in linear matrix inequality (LMI) regions, a class of convex regions of the complex plane that embraces most practically useful stability regions. The focus is on linear systems with static uncertainty on the state matrix. For this class of uncertain systems, the notion of quadratic stability and the related robustness analysis tests are generalized to arbitrary LMI regions. The resulting tests for robust pole clustering are all numerically tractable because they involve solving linear matrix inequalities (LMIs) and cover both unstructured and parameter uncertainty. These analysis results are then applied to the synthesis of dynamic output-feedback controllers that robustly assign the closed-loop poles in a prescribed LMI region. With some conservatism, this problem is again tractable via LMI optimization. In addition, robust pole placement can be combined with other control objectives, such as H/sub 2/ or H/sub /spl infin// performance, to capture realistic sets of design specifications. Physically motivated examples demonstrate the effectiveness of this robust pole clustering technique.
ISSN:0018-9286
1558-2523
DOI:10.1109/9.811208