Aeroelastic Reduced Order Model with State Consistence Enforcement

Shu, Jung I.; Wang, Yi; Krolick, William C.; Pant, Kapil

doi:10.2514/6.2022-0990

Cited by 4 publications

(3 citation statements)

References 20 publications

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“…Firstly, the oblique projection matrix sequences {Π i (ρ k )} n g i=1 in all subsets are classified into two groups based on whether they should be truncated or reserved. Usually, eigenvalues with low frequencies contribute more to system dynamics, and the related subsets are grouped into a new subset r to be reserved, while the remaining subsets t are to be truncated, as written in Equation (27).…”

Section: Reconstruction Of the Consistent Transformationsmentioning

confidence: 99%

“…The implementation of the existing modal matching method mentioned above consists of two steps [27][28][29]. Firstly, a metric function is constructed to compute the distance between the eigenvalues of adjacent local models.…”

Section: Introductionmentioning

confidence: 99%

“…Note that transformation matrices V t (ρ k ) and W t (ρ k ) are derived by the oblique projection Π t(ρ k ), which is complementary to Π r (ρ k ) in Equation (27). Considering the frequency range that the flight dynamics and structural dynamics mainly contribute to, the system frequency of the reduced-order LPV model was limited to the range from 0.1 Hz to 50 Hz.…”

mentioning

confidence: 99%

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Oblique Projection-Based Modal Matching Algorithm for LPV Model Order Reduction of Aeroservoelastic Systems

Liu

Gao

et al. 2023

Aerospace

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An aeroservoelastic system can be described as a gridding-based linear parameter-varying (LPV) model, whose dynamic characteristics usually vary with the airspeed. Due to the high order of the system, it is necessary to perform order reduction on LPV models to overcome the control design challenges. However, when directly extending linear time-invariant (LTI) model order reduction technologies to the LPV system, states of the reduced-order LTI models generated separately at different grid points could be inconsistent. In this paper, a novel modal matching algorithm is proposed to solve the problem of state inconsistency by identifying the internal connection between the models at adjacent grid points. An oblique projection-based distance metric is defined to improve the reliability of the modal matching algorithm. The reduced-order LPV model constructed based on this method would have a high fidelity relative to the original model and a smooth interpolation performance between grid points. The proposed algorithm is applied to the X-56A aircraft, and numerical results show its effectiveness.

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Section: Reconstruction Of the Consistent Transformationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Oblique Projection-Based Modal Matching Algorithm for LPV Model Order Reduction of Aeroservoelastic Systems

Liu

Gao

et al. 2023

Aerospace

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Genetic-Algorithm-Guided Development of Parametric Aeroelastic Reduced-Order Models with State-Consistence Enforcement

Shu¹,

Wang²,

Brown³

et al. 2023

AIAA Journal

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Data-driven parametric reduced-order models (ROMs) in state-space form are valuable tools for rapid aeroelastic (AE) analysis and aerostructure control synthesis. However, the issue of state inconsistence (significant variations in model parameters over tradespaces) makes ROMs noninterpolatable, and therefore unable to accommodate use over broad flight parameter space. This paper presents a holistic framework that combines a system identification technique with state-consistence enforcement (SCE) and a genetic algorithm (GA) for the automated development of interpolatable AE ROMs across broad flight regimes. The SCE technique introduces a regularization term to the AutoRegressive model with eXogenous inputs (ARX) to specifically penalize model parameter variation between flight conditions. The GA autonomously guides the ROM development process toward optimal SCE-ARX hyperparameter selection that balances between model parameter variations and ROM accuracy. The GA-guided SCE-ARX approach is applied to build a parametric AE-ROM database at selected flight conditions, which, because of its state consistence, can be interpolated to create ROMs at any interstitial conditions, where training data or ROMs are not initially available, hence rapidly establishing the full coverage of the entire parameter space. The ROMs generated by the proposed method are compared with those by ARX, SCE, and GA-guided ARX in prediction accuracy. The individual and combined effects of SCE and GA on model parameter variation and ROM interpolatability are thoroughly investigated. The present method demonstrates the most accurate and robust performance for parametric ROM construction across the broad flight envelope.

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Genetic Algorithm-Guided Parametric Aeroelastic Reduced-Order Model with State-Consistence Enforcement

Shu

Wang

Krolick

et al. 2023

AIAA SCITECH 2023 Forum

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Aeroelastic Reduced Order Model with State Consistence Enforcement

Cited by 4 publications

References 20 publications

Oblique Projection-Based Modal Matching Algorithm for LPV Model Order Reduction of Aeroservoelastic Systems

Oblique Projection-Based Modal Matching Algorithm for LPV Model Order Reduction of Aeroservoelastic Systems

Genetic-Algorithm-Guided Development of Parametric Aeroelastic Reduced-Order Models with State-Consistence Enforcement

Genetic Algorithm-Guided Parametric Aeroelastic Reduced-Order Model with State-Consistence Enforcement

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