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- W2478585022 abstract "LPV control has emerged as a systematic approach in the design of gain-scheduled controllers. This requires the identification of LPV models. The aim of this paper is to develope a flexible and accurate 2D-LRM approach, to enable fast and accurate non-parametric system identification of a frequency response function. The scope of this paper is on the identification of open-loop SISO LPV systems. Smoothness between several frozen LTI conditions within the LPV system is exploited to enable accurate pre-testing for parametric LPV modeling. The proposed approach achieves smoother estimations of the LPV behavior without an increase in estimation errors and with reduced variances. Traditional LPM and LRM approaches can be recovered as a special case of the proposed approach. The potential of the approach is shown by virtue of a simulation of a medical X-ray system." @default.
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- W2478585022 date "2016-07-01" @default.
- W2478585022 modified "2023-09-25" @default.
- W2478585022 title "Frequency response function identification of LPV systems: A 2D-LRM approach with application to a medical X-ray system" @default.
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- W2478585022 doi "https://doi.org/10.1109/acc.2016.7526077" @default.
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