Randomized algorithms for robust control analysis and synthesis have polynomial complexity

We consider several robust control analysis and design problems. As has become well known over the last few years, most of these problems are NP hard. We show that if instead of worst-case guaranteed conclusions, one is willing to draw conclusions with a high degree of confidence, then the computati...

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Bibliographic Details
Published inProceedings of 35th IEEE Conference on Decision and Control Vol. 3; pp. 3470 - 3475 vol.3
Main Authors Khargonekar, P., Tikku, A.
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 1996
Subjects
Algorithm design and analysis
Centralized control
Computational complexity
Control theory
Polynomials
Probability distribution
Robust control
Robust stability
Robustness
Uncertainty
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Summary:We consider several robust control analysis and design problems. As has become well known over the last few years, most of these problems are NP hard. We show that if instead of worst-case guaranteed conclusions, one is willing to draw conclusions with a high degree of confidence, then the computational complexity decreases dramatically.
ISBN:9780780335905
0780335902
ISSN:0191-2216
DOI:10.1109/CDC.1996.573700