2006•Unpublished venueRequires access

An LFT approach to robust gain scheduling

J.-F. Magni

Open publisher page 11 citations

Abstract

Traditionally, scheduled controllers are obtained by interpolation of a bank of linear feedback gains. The strategy adopted here is quite different as the controller is directly designed in scheduled form. The key idea consists of designing the feedback gain in LFT (Linear Fractional Transformation) form, the system to be controlled being itself in LFT form. Using an observer-based scheduled feedback and the corresponding Q-parameterization, robust control design can be treated by alternating μ-analysis for worst case identification and multimodel control for simultaneous treatment of the worst cases.

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What this paper is about

Traditionally, scheduled controllers are obtained by interpolation of a bank of linear feedback gains. The strategy adopted here is quite different as the controller is directly designed in scheduled form. The key idea consists of designing the feedback gain in LFT (Linear Fractional Transformation) form, the system to be controlled being itself in LFT form. Using an observer-based scheduled feedback and the corresponding Q-parameterization, robust control design can be treated by alternating μ-analysis for worst case identification and multimodel control for simultaneous treatment of the worst cases.

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Available abstract

Traditionally, scheduled controllers are obtained by interpolation of a bank of linear feedback gains. The strategy adopted here is quite different as the controller is directly designed in scheduled form. The key idea consists of designing the feedback gain in LFT (Linear Fractional Transformation) form, the system to be controlled being itself in LFT form. Using an observer-based scheduled feedback and the corresponding Q-parameterization, robust control design can be treated by alternating μ-analysis for worst case identification and multimodel control for simultaneous treatment of the worst cases.

Key concepts: Linear fractional transformation, Control theory (sociology), Gain scheduling, Robust control, Computer science, Control engineering, Scheduling (production processes), Controller (irrigation)

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