2011•Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace EngineeringRequires access

Linear fractional transformation gain-scheduling flight control preserving robust performance

Nabil Aouf, Benoît Boulet

Open publisher page 6 citations

Abstract

In this article, a gain-scheduling flight controller design based on a blending/interpolating methodology and an optimal linear fractional transformation (LFT)-based control technique is proposed to achieve robust performances over a wide range of aircraft operating conditions. Representing the non-linear system dynamics into an uncertain LFT system form, our gain-scheduling strategy designs a limited number of robust linear controllers covering the whole range of operating conditions. Using these fixed controllers in a robust performance control set-up, we derive a blending/interpolating scheduling controller, which achieves the desired performance for the entire flight envelope. Our approach offers the benefit of facilitating controller design and provides proofs of robust stability and performance through an uncertain LFT robust performance formulation. In addition, tools analysing the robustness of the closed-loop gain-scheduling system are also provided. Non-linear simulations based on our proposed approach for a B1 flexible aircraft for a limited flight but reasonable flight envelope show very good performance results in both time and frequency domain responses.

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What this paper is about

In this article, a gain-scheduling flight controller design based on a blending/interpolating methodology and an optimal linear fractional transformation (LFT)-based control technique is proposed to achieve robust performances over a wide range of aircraft operating conditions. Representing the non-linear system dynamics into an uncertain LFT system form, our gain-scheduling strategy designs a limited number of robust linear controllers covering the whole range of operating conditions. Using these fixed controllers in a robust performance control set-up, we derive a blending/interpolating scheduling controller, which achieves the desired performance for the entire flight envelope. Our approach offers the benefit of facilitating controller design and provides proofs of robust stability and performance through an uncertain LFT robust performance formulation. In addition, tools analysing the robustness of the closed-loop gain-scheduling system are also provided. Non-linear simulations based on our proposed approach for a B1 flexible aircraft for a limited flight but reasonable flight envelope show very good performance results in both time and frequency domain responses.

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OpenAlex reports 6 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In this article, a gain-scheduling flight controller design based on a blending/interpolating methodology and an optimal linear fractional transformation (LFT)-based control technique is proposed to achieve robust performances over a wide range of aircraft operating conditions. Representing the non-linear system dynamics into an uncertain LFT system form, our gain-scheduling strategy designs a limited number of robust linear controllers covering the whole range of operating conditions. Using these fixed controllers in a robust performance control set-up, we derive a blending/interpolating scheduling controller, which achieves the desired performance for the entire flight envelope. Our approach offers the benefit of facilitating controller design and provides proofs of robust stability and performance through an uncertain LFT robust performance formulation. In addition, tools analysing the robustness of the closed-loop gain-scheduling system are also provided. Non-linear simulations based on our proposed approach for a B1 flexible aircraft for a limited flight but reasonable flight envelope show very good performance results in both time and frequency domain responses.

Key concepts: Linear fractional transformation, Gain scheduling, Flight envelope, Control theory (sociology), Robustness (evolution), Scheduling (production processes), Robust control, Computer science

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