Simulation and Optimization of Takeoff Maneuvers of Very Flexible Aircraft

Carre, Alfonso del; Palacios, Rafael

doi:10.2514/1.c035901

Cited by 12 publications

(5 citation statements)

References 28 publications

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“…Helios aerial disintegration Zephyr S wing breakage Aquila landing crash In the structural and flight dynamic modeling of solarpowered UAVs, multirigid body, flexible beam, and finite element models have different advantages, and the flexible beam theory is widely used for its ability to take into account the dynamic characteristics and computational cost, and the representatives are displacement formulation [20], intrinsic formulation [21][22][23], or strain formulation [24][25][26]. Voß et al [27] used an intrinsic beam model to analyze the challenges of flight envelope boundaries on structural safety and presented the changing weight of aeroelastic analysis in the design of solar-powered UAVs.…”

Section: Helios Zephyr S Aquilamentioning

confidence: 99%

Comparative Study and Airspeed Sensitivity Analysis of Full-Wing Solar-Powered UAVs Using Rigid-Body, Multibody, and Rigid-Flexible Combo Models

Guo,

Mu,

Zhou

et al. 2024

International Journal of Aerospace Engineering

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Solar-powered UAVs are characterized by large-scale, lightweight, and low airspeed, and changes in airspeed lead to wing deformation or stalling, which can easily induce serious flight accidents. A single dynamic model cannot accurately describe this feature, and this airspeed sensitivity can only be analyzed by integrating rigid-body, multirigid-body, and rigid-flexible combo models. This paper proposes a dynamic analysis method for a mixture of rigid-body, multirigid-body, and rigid-flexible combo models, considering the applicable airspeed ranges, computational costs, and structural deformation assumptions of the three models and comparing the differences of modes and responses at different airspeeds, and quantitatively analyzes the effects of airspeed on the motion, deformation, and coupling. The results show that appropriate increase of airspeed is beneficial to the stability of large-scale lightweight platforms, but when it is increased to more than two times the cruise speed, the structural deformation is coupled with the flight dynamic modes, leading to the deterioration of the overall dynamic response. Finally, a mixture of the three models at different airspeeds is proposed, which is necessary for future ultralarge-scale solar-powered UAVs.

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Section: Helios Zephyr S Aquilamentioning

confidence: 99%

Comparative Study and Airspeed Sensitivity Analysis of Full-Wing Solar-Powered UAVs Using Rigid-Body, Multibody, and Rigid-Flexible Combo Models

Guo,

Mu,

Zhou

et al. 2024

International Journal of Aerospace Engineering

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“…Bayesian optimization [31] is well-suited to find the optimal (maximum cost) location to add points to the training set, since it does not assume anything about the underlying cost function (which is expensive to evaluate) and does not compute derivatives. The successful optimization of takeoff maneuvers in SHARPy using BO [32] showcases the advantages of this method, hence we seek to use it for this problem.…”

Section: Optimal Sampling Using Bayesian Optimizationmentioning

confidence: 99%

Fast flutter evaluation of very flexible wing using interpolation on an optimal training dataset

Goizueta

Wynn

Palacios

2022

AIAA SCITECH 2022 Forum

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Machine learning strategies can be efficiently used to accelerate the exploration of the design space or flight envelope of highly flexible aeroelastic systems. In this paper, we explore the use of interpolation between parametric state-space realizations to, with few true systems sampled in the parameter space, produce with adequate accuracy a state-space model anywhere in the parameter space. The location of the sampling points is shown to be decisive thus the selection of these points takes the focus in this work. Several approaches are explored, putting emphasis on adaptive schemes that locate the optimal points in the parameter space that are needed to capture the changing system dynamics. Since the evaluation of the true system is costly, optimization techniques based on statistical surrogate models are sought, which need to be trained but are effective in locating the best locations to use as sampling data. A novel method inspired by Bayesian optimization is used to make the most out of a limited number of known state-spaces by taking different combinations as training and testing data of the statistical surrogate, leading to not only an accurate interpolation framework but also to a reduction of 50% of the number of costly full system evaluations compared to a standard Bayesian optimization set-up. These methods are demonstrated on the Pazy wing, a very flexible wing with a complex stability envelope, whereby we produce a very accurate representation of the flutter envelope at a reduced computational cost.

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“…Although very compelling results have been obtained in these works, where the framework has been also applied to higher dimensional systems than those used to equip the internal models, the former were still based on the same underlying equations. Here, application of the proposed methods to directly control SHARPy simulations offers the possibility to test them in much more realistic conditions [16,39,40], assessing the plausibility of real-context application.…”

Section: Numerical Examplesmentioning

confidence: 99%

Proof of Concept for a Hardware-in-the-Loop Nonlinear Control Framework for Very Flexible Aircraft

Artola

Goizueta

Wynn

et al. 2021

AIAA Scitech 2021 Forum

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Nonlinear Moving Horizon Estimation (MHE) and Model Predictive Control (MPC) strategies for very flexible aircraft are presented. They are underpinned by a nonlinear reduced-order model built upon the structure's natural modes of vibration. This internal model aims for a minimal realisation of the aircraft which retains sufficient information to enable efficient real-time estimation and control. It is based on a modal intrinsic description of geometrically-nonlinear beams and a linearised unsteady vortex lattice aerodynamic model. Numerical evidence has shown that models of this form are able to capture the main nonlinear geometrical couplings at a very low computational cost. This opens the door to MHE and MPC strategies, which are naturally more computationally demanding than other linear conventional strategies, but are more versatile and able to provide control in the usually neglected nonlinear regime. The proposed control framework is tested on models built in an in-house open-source nonlinear aeroelasticity simulation and analysis package, to emulate the controller performance on a realistic plant model. Very satisfactory results are obtained in a flutter suppression problem involving a very flexible clamped wing, where the nonlinearity of the problem is leveraged by the internal model to achieve stabilisation, and a payload drop control of a very flexible HALE aircraft.

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Simulation and Optimization of Takeoff Maneuvers of Very Flexible Aircraft

Cited by 12 publications

References 28 publications

Comparative Study and Airspeed Sensitivity Analysis of Full-Wing Solar-Powered UAVs Using Rigid-Body, Multibody, and Rigid-Flexible Combo Models

Comparative Study and Airspeed Sensitivity Analysis of Full-Wing Solar-Powered UAVs Using Rigid-Body, Multibody, and Rigid-Flexible Combo Models

Fast flutter evaluation of very flexible wing using interpolation on an optimal training dataset

Proof of Concept for a Hardware-in-the-Loop Nonlinear Control Framework for Very Flexible Aircraft

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