Method to Account for Estimator-Induced Previewed Information Losses - Application to Synthesis of Lidar-Based Gust Load Alleviation Functions

Davide Cavaliere; Nicolas Fezans; Daniel Kiehn

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CEAS EuroGNC 2022

Method to Account for Estimator-Induced Previewed Information Losses - Application to Synthesis of Lidar-Based Gust Load Alleviation Functions

Davide Cavaliere	PhD Researcher, DLR (German Aerospace Center), Institute of Flight Systems, 38108 Braunschweig, Germany.
Nicolas Fezans	Scientific Advisor, DLR (German Aerospace Center), Institute of Flight Systems, 38108 Braunschweig, Germany.
Daniel Kiehn	Research Scientist, DLR (German Aerospace Center), Institute of Flight Systems, 38108 Braunschweig, Germany.

Abstract:
Preview control using wind estimates derived from Doppler wind lidar measurements is a promising technique for designing active gust load alleviation functions. Due to high noise levels in the lidar measurements, the associated estimator must use some type of smoothing to obtain a reasonable estimate, which entails a loss of some information. Taking this loss into account during control synthesis should help ease the tuning procedure and improve the performance and robustness of the resulting controller. This paper proposes a method to consistently design a linear filter which closely approximates the behavior of the wind estimator and which can be integrated into a linear robust control framework. Its characteristics are shown to closely match the real estimator over a range of types of turbulence using a standard set of system parameters, and in a control synthesis example, it demonstrates a significant improvement in load alleviation performance.

Keywords: Preview control; Lidar-based gust load alleviation; Robust control; Estimation losses

View PDF CEAS-GNC-2022-063

Davide Cavaliere, Nicolas Fezans, Daniel Kiehn: Method to Account for Estimator-Induced Previewed Information Losses - Application to Synthesis of Lidar-Based Gust Load Alleviation Functions. Proceedings of the 2022 CEAS EuroGNC conference. Berlin, Germany. May 2022. CEAS-GNC-2022-063.

BibTeX entry:

@Incollection{CEAS-GNC-2022-063,

    authors = {Cavaliere, Davide and Fezans, Nicolas and Kiehn, Daniel},

    title = {Method to Account for Estimator-Induced Previewed Information Losses - Application to Synthesis of Lidar-Based Gust Load Alleviation Functions},

    booktitle = {Proceedings of the 2022 {CEAS EuroGNC} conference},

    address = {Berlin, Germany},

    month = may,

    year = {2022},

    note = {CEAS-GNC-2022-063}

}