Adaptive Incremental Nonlinear Dynamic Inversion Flight Control for Consistent Handling Qualities

Conference Paper (2022)
Author(s)

B Smit (student) (Student TU Delft)

T.S.C. Pollack (TU Delft - Control & Simulation)

Erik-Jan Van Kampen (TU Delft - Control & Simulation)

Research Group
Control & Simulation
Copyright
© 2022 B. Smit, T.S.C. Pollack, E. van Kampen
DOI related publication
https://doi.org/10.2514/6.2022-1394
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 B. Smit, T.S.C. Pollack, E. van Kampen
Research Group
Control & Simulation
ISBN (electronic)
978-1-62410-631-6
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Control augmentation systems based on Incremental Nonlinear Dynamic Inversion (INDI) are able to provide high-performance nonlinear control without a holistic model. Considering an angular rate control law for a fixed-wing aircraft, only a control effectiveness (CE) model and angular acceleration measurement feedback is required. Despite enhanced robustness against parametric model mismatches due to reduced model dependency, the performance of INDI-based control laws can still vary due to inaccurate CE models. This paper confirms that longitudinal centre of gravity (CG) shifts and CE uncertainty result in varying handling qualities and stability (HQ\&S) characteristics. An adaptive solution using Least-Mean-Square (LMS) based parameter estimation is investigated to address these variations. The results demonstrate that online CE model correction result in reduced HQ\&S variation. However, it was found that some flight conditions together with adverse CG shifts could lead to violation of the time-scale separation assumption that underlies the adaptive control law design. As this assumption is inherent to the INDI control design itself as well, online CE model correction is only partly able to resolve the resulting performance variations.

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