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Efficient Design of Low-Order H-infinity Optimal Controllers Using Evolutionary Algorithms and a Bisection Approach
Citation Link: https://doi.org/10.15480/882.247
Publikationstyp
Conference Paper
Date Issued
2006
Sprache
English
Author(s)
Institut
TORE-DOI
Citation
Proceedings of the 2006 IEEE International Conference on Computer Aided Control Systems Design
This paper considers a hybrid evolutionary algebraic approach to the non-convex problem of designing low-order H-infinity optimal controllers. It is shown that using the closed-loop H-infinity norm as fitness measure in a population-based,
evolutionary search does not require the computation of the H-infinity norm for each controller of the population. Instead, the fact that evolutionary algorithms assign fitness measures to individuals based on a ranking is exploited and a bisection approach is proposed that allows to trade accuracy that is not needed against computational efficiency without loosing information. Three design examples are used to illustrate the improvement in computational speed achieved with the proposed method.
Copyright note: ©20xx IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
evolutionary search does not require the computation of the H-infinity norm for each controller of the population. Instead, the fact that evolutionary algorithms assign fitness measures to individuals based on a ranking is exploited and a bisection approach is proposed that allows to trade accuracy that is not needed against computational efficiency without loosing information. Three design examples are used to illustrate the improvement in computational speed achieved with the proposed method.
Copyright note: ©20xx IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Subjects
Robust Control
Evolutionary Algorithms
Ranking Selection
H-infinity
Bisection
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