Optimal Control for Distributed Aeroelastic Morphing Structure with Uncertainties and Imperfections

T. Mkhoyan*, Xuerui Wang, R. De Breuker

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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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
Original languageEnglish
Title of host publicationProceedings of the AIAA SCITECH 2024 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc. (AIAA)
Number of pages23
ISBN (Electronic)978-1-62410-711-5
DOIs
Publication statusPublished - 2024
EventAIAA SCITECH 2024 Forum - Orlando, United States
Duration: 8 Jan 202412 Jan 2024

Conference

ConferenceAIAA SCITECH 2024 Forum
Country/TerritoryUnited States
CityOrlando
Period8/01/2412/01/24

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