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Complexity of LPV Models

Controller design based on linear parameter-varying (LPV) models has received considerable attention over the last 15 years. This approach provides a systematic alternative to the heuristic design of gain-scheduled controllers, and it allows the extension of familiar linear control techniques to nonlinear systems. However, the complexity of LPV models turns out to be a major challenge. For efficient controller synthesis, LPV models are preferred that are affine in the scheduling parameters and of low complexity. We consider the complexity of LPV models under two aspects: the number of state variables and the number of scheduling parameters. The number of scheduling parameters can be reduced by applying a coordinate transformation to the parameter space based on Principal Component Analysis. As for the model order, we present a method for frequency weighted balanced truncation of LPV models that fixes two shortcomings of previous results: stability of the reduced model is maintained, and a bound on the modelling error is provided.
Type of Seminar:
IfA Seminar
Prof. Herbert Werner
Hamburg University of Technology, Institute of Control Systems
Mar 16, 2010   14:00

ETL K 25
Contact Person:

Thomas Besselmann
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