Optimal Control for Distributed Aeroelastic Morphing Structure with Uncertainties and Imperfections

Conference Paper (2024)
Author(s)

T. Mkhoyan (TU Delft - Arts & Crafts)

Xuerui Wang (TU Delft - Aerospace Engineering)

R. De Breuker (TU Delft - Aerospace Engineering)

Research Group
Arts & Crafts
DOI related publication
https://doi.org/10.2514/6.2024-0832 Final published version
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Publication Year
2024
Language
English
Research Group
Arts & Crafts
Article number
AIAA 2024-0832
ISBN (electronic)
978-1-62410-711-5
Event
AIAA SCITECH 2024 Forum (2024-01-08 - 2024-01-12), Orlando, United States
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Abstract

This research takes a further step towards the development of an autonomous aeroservoelastic wing concept with distributed flaps. The wing demonstrator, developed within the TU Delft SmartX project, aims to demonstrate in-flight performance optimization and multi-objective control using an over-actuated wing design. To address the challenges posed by the aeroelastic system’s nonlinearities and uncertainties, this paper employs an optimal control method relying on solving the State-Dependent Riccati Equation (SDRE). Geometrical nonlinearities, introduced in the form of plunge and torsion stiffness, make the system state-dependent and unsuitable for linear control methods. Additionally, a backlash model is incorporated to represent the uncertainty of the actuation system. The control strategy is implemented in a multi-objective manner to perform maneuver and gust load alleviation while accounting for the nonlinearities and uncertainties using the SDRE control. Firstly, a numerical sample case is investigated involving a state-dependent and highly non-linear canard aircraft configuration, to assess the ability of the SDRE control method. Then, in a numerical experiment, the effectiveness of the control strategy is evaluated through the nonlinear aeroelastic model. Evaluations are made on the practicality of the control approach, laying a foundation for future static and dynamic wind tunnel experiments with the SmartX-Neo demonstrator.

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