Aeroservoelastic Structural and Control Optimization Using Robust Design Schemes

General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms Features that complicate its study are the presence of multiple modal instabilities, and the dierent inuence that system parameters have on each of them. The robust analysis framework based on Linear Fractional Transformation modeling and structured singular value µ analysis is used in this work to study the BFF problem in a systematic way. The analyses performed showcase the potential of these methods, not only in supplying a characterization of the system in terms of its robustness, but also in gaining further understanding of the BFF problem and reconciling the results with physical features. It is also shown that the robust modeling analysis framework complements the conventional, state of practice, methods while allowing the study of highly coupled systems (of which the exible aircraft is an example) to be addressed in an incremental and methodological manner.

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“…Further, in [25] their application to the structural and control optimization problem of an aeroservoelastic system was presented.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Study of Flexible Aircraft Body Freedom Flutter with Robustness Tools

Iannelli

Marcos

Lowenberg

2018

Journal of Guidance, Control, and Dynamics

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“…The use of fixed-basis state-space aeroservoelastic models in aircraft design with dynamic stability and response considerations is detailed in [21], [42], and [44]. The computational efficiency of the design optimization process is obviously affected by the order n of the state-space model, with the CPU time proportional to n 2 to n 3 .…”

Section: Dynamic Aeroservoelastic Stability and Responsementioning

confidence: 99%

Procedures and Models for Aeroservoelastic Analysis and Design

Karpel

2001

Z. angew. Math. Mech.

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The multi‐disciplinary area that deals with the interaction of the structural, aerodynamic, and control systems of flight vehicles is called aeroservoelasticity. The various aircraft design aspects which are affected by aeroservoelastic interaction are presented with a common modal‐based formulation. The disciplinary and interaction techniques are reviewed and combined for an integrated design optimization scheme where stress, static‐aeroelastic, closed‐loop flutter, control margins, time response, and continuous gust constraints are treated with a common basic model. The structure is represented in the basic model by a set of low‐frequency normal modes of a baseline design. Design changes are adequately addressed without changing the generalized coordinates. Typical difficulties of the modal approach are alleviated by various optional fictitious‐mass and modal perturbation techniques. Static modes can be added during the optimization process for better convergence to the optimal solution. Minimum‐state rational approximation of the unsteady aerodynamics leads to an efficient state‐space model which can be augmented by any combination of linear control components. Physical weighting algorithm is used to improve the aerodynamic approximations and to select modes for truncation or residualization. Linear reduced‐size models and the associated analytic sensitivities to design changes facilitate extremely efficient and adequately accurate on‐line design sessions. The linear models can be integrated with computational aerodynamics codes for the evaluation of important non‐linear aerodynamic effects early in the design process.

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“…Eigenvalue analysis was then performed on the structure, obtaining the structural modes in the intrinsic formulation defined on the 124 nodes on the airframe using the procedure outlined in Wang et al 30 The payload is considered part of the model, thus varying the payload requires re-computing the modes. It is worth noting that Moulin et al 31 demonstrated a method in which this is avoided but this is not investigated here. The natural modes and frequency information leads to the A, Λ matrices and Γ coefficients in (34).…”

Section: Ivb1 Test Case Descriptionmentioning

confidence: 99%