H∞ Control Design for Active Flutter Suppression of Flexible-Wing Unmanned Aerial Vehicle Demonstrator

Waitman, Sérgio; Marcos, Andrés

doi:10.2514/1.g004618

Cited by 20 publications

(10 citation statements)

References 26 publications

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“…Such approach leads to high computational load of the LMI optimization. [39] proposed an LTI H ∞ method for the FLEXOP aircraft flutter suppression. [40] uses H 2 optimal blends of the input and output signals for aeroelastic mode control, also based on LTI models.…”

Section: Flutter Suppression Controlmentioning

confidence: 99%

Robust control design for the FLEXOP demonstrator aircraft via tensor product models

Takarics

Vanek

2021

Asian Journal of Control

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The paper proposes a control design methodology for active flutter suppression for the aeroservoelastic (ASE) aircraft of the European project FLEXOP. The aim of the controller is to robustly stabilize the aeroelastic modes. The control design is based on a control‐oriented linear parameter‐varying (LPV) model, which is derived via “bottom–up” modeling approach and includes the parametric uncertainties of the flutter modes. The tensor product (TP) type LPV model is generated via TP model transformation. The symmetric and asymmetric flutter modes are decoupled, which allows independent control design for each. LPV observer‐based state feedback control structure is applied with constraints on the maximal control value to avoid input saturation. The scheduling parameters of the TP‐type LPV models are split into measured and uncertain parameters for robust control design. Convex hull manipulation‐based optimization and model complexity effects are investigated. The resulting controller is validated via the high‐fidelity ASE model of the FLEXOP aircraft.

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Section: Flutter Suppression Controlmentioning

confidence: 99%

Robust control design for the FLEXOP demonstrator aircraft via tensor product models

Takarics

Vanek

2021

Asian Journal of Control

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“…In this section, the control design activities by UBRISTOL are summarized. They are presented in more detail in references [7,33,34] to which the reader is referred.…”

Section: Standard and Structured H ∞ Flutter Controlmentioning

confidence: 99%

“…For the final design, see reference [34] for details, three LTI controllers were obtained using the same synthesis plant interconnection as in Figure 15 but for three 59, 63, 66 m/sec (plant numbers N = 15, 19, 22 respectively). In addition to the change of plants used for the LTI design, which already resulted in different values for the weights, a disturbance weight that was used before during the consolidated interconnection synthesis was now removed in order to reduce the overall complexity of the tuning process.…”

Section: Final Scheduled Coupled Standard H ∞ Design Stepmentioning

confidence: 99%

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Active Flutter Mitigation Testing on the FLEXOP Demonstrator Aircraft

Takarics

Patartics

Luspay

et al. 2020

AIAA Scitech 2020 Forum

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The paper details the research and corresponding implementation and testing steps of the FLEXOP demonstrator aircraft. Within the EU funded project an unmanned demonstrator aircraft is built to validate the mathematical modelling, flight control design and implementation side of active flutter mitigation. In order to validate the different methods and tools developed in this project, a flight test campaign is planned, in which the design and manufacturing of stiff wings (-0), are compared with very flexible wings (-1) with active flutter control, to see the overall benefit vs. risk of such technology. The mathematical models of the aircraft are first developed using FEM and CFD tools, what are later reduced by model order reduction techniques. The high-fidelity models are updated using Ground Vibration Test results. Manufacturing tolerances and variations in aircraft parameters are captured by systematic modelling of parametric and dynamic uncertainties. Both the simulation environment and the control design framework use different modelling fidelity, what are described within the paper. Reduced models are developed using two distinctive methods, respecting the control design needs: top-down balanced LPV reduction and bottom-up structure preserving methods. Based on the reduced order models various control design techniques have been elaborated by the consortium partners. In particular DLR developed and implemented a modal control method using H2 optimal blends for inputs and outputs. University of Bristol developed structured H-infinity optimal control methods, while SZTAKI proposed a worst-case gain optimal method structured controller synthesis method handling parametric and complex uncertainties. After the brief introduction of hardware-in-the-loop test setup and the description of mission scenarios the implementation issues of the baseline and flutter controllers are discussed. DLR and SZTAKI flutter controllers are evaluated in a hybrid software-/ hardware-in-the-loop test setup as at this stage of development the latter can not tolerate the estimated delay of the hardware system but their comparison is advantageous before future developments. Recommendations on active flutter mitigation methods are given based on the experience of synthesis and implementation of these controllers. Flight test results will follow these experiments, once the flight testing of the flutter wing commences.

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“…Then, the controller is designed considering a polytopic LPV representation. In the work proposed by Waitman and Marcos [20], a high-fidelity, nonlinear aeroservoelastic model of the FLEXOP aircraft was considered, and three H ∞ optimal controllers were tuned and scheduled for different true airspeed values, increasing the damping of the flutter modes at these velocities. This approach led to a flutter boundary increase of 30%.…”

Section: Introductionmentioning

confidence: 99%

Computational Analysis of the Active Control of Incompressible Airfoil Flutter Vibration Using a Piezoelectric V-Stack Actuator

Vindigni¹,

Orlando

Milazzo

2021

Vibration

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The flutter phenomenon is a potentially destructive aeroelastic vibration studied for the design of aircraft structures as it limits the flight envelope of the aircraft. The aim of this work is to propose a heuristic design of a piezoelectric actuator-based controller for flutter vibration suppression in order to extend the allowable speed range of the structure. Based on the numerical model of a three degrees of freedom (3DOF) airfoil and taking into account the FEM model of a V-stack piezoelectric actuator, a filtered PID controller is tuned using the population decline swarm optimizer PDSO algorithm, and gain scheduling (GS) of the controller parameters is used to make the control adaptive in velocity. Numerical simulations are discussed to study the performance of the controller in the presence of external disturbances.

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H∞ Control Design for Active Flutter Suppression of Flexible-Wing Unmanned Aerial Vehicle Demonstrator

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Cited by 20 publications

References 26 publications

Robust control design for the FLEXOP demonstrator aircraft via tensor product models

Robust control design for the FLEXOP demonstrator aircraft via tensor product models

Active Flutter Mitigation Testing on the FLEXOP Demonstrator Aircraft

Computational Analysis of the Active Control of Incompressible Airfoil Flutter Vibration Using a Piezoelectric V-Stack Actuator

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