Chaotic motions of an airfoil with non-linear stiffness in incompressible flow

Zhao, Lin; Yang, Zhichun

doi:10.1016/0022-460x(90)90541-7

Cited by 133 publications

(66 citation statements)

References 6 publications

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“…Although, several classes of non-linear mappings for stiffness contributions k α (α) have been investigated for open loop dynamics of aeroelastic systems, 17,18,19,20 the work of O'Neil et al 15,16 demonstrated that a polynomial mapping of the form…”

Section: Non-linear Pitch-plunge Model Of Aircraft Dynamicsmentioning

confidence: 99%

Non-Linear System Identification for Aeroelastic Systems with Application to Experimental Data

Kukreja

2008

AIAA Guidance, Navigation and Control Conference and Exhibit

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Representation and identification of a non-linear aeroelastic pitch-plunge system as a model of the NAR-MAX class is considered. A non-linear difference equation describing this aircraft model is derived theoretically and shown to be of the NARMAX form. Identification methods for NARMAX models are applied to aeroelastic dynamics and its properties demonstrated via continuous-time simulations of experimental conditions. Simulation results show that (i) the outputs of the NARMAX model match closely those generated using continuous-time methods and (ii) NARMAX identification methods applied to aeroelastic dynamics provide accurate discrete-time parameter estimates. Application of NARMAX identification to experimental pitchplunge dynamics data gives a high percent fit for cross-validated data.

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Section: Non-linear Pitch-plunge Model Of Aircraft Dynamicsmentioning

confidence: 99%

Non-Linear System Identification for Aeroelastic Systems with Application to Experimental Data

Kukreja

2008

AIAA Guidance, Navigation and Control Conference and Exhibit

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“…Semi-empirical procedures combined with experimental data were used to predict the joint strength as a function of basic laminate properties and joint geometrical parameters. Studies reported in the literature address the importance of joint allowables [27,28], selection of optimum ply stacking sequence [8], washer size, effects of clamping force or bolt preload on joint strength and failure modes [9,29,30]. Yet, some of these questions remain unanswered.…”

Section: Design Analysis and Characterization Of Jointsmentioning

confidence: 99%

Simple Questions for Interactive Information Retrieval

Kumaran

Allan

2006

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“…Further, c α and c h respectively are the pitch and plunge structural damping coefficients, and k h is the plunge structural spring constant. Several classes of non-linear stiffness contributions k α (α) have been studied in papers treating the open-loop dynamics of aeroelastic systems [2,18,19,7]. For purposes of illustration, we now introduce the use of polynomial non-linearities:…”

Section: Equations Of Motionmentioning

confidence: 99%

“…Regarding the properties of aeroelastic systems one can find the study of free-play non-linearity by Tang and Dowell in [2,3], by Price et al in [4] and [5], by Lee et al in [6], and a complete study of a class of non-linearities is in [7], [5]. O'Neil et al [8] examined the continuous structural non-linearity of aeroelastic systems.…”

Section: Introductionmentioning

confidence: 99%

Global Asymptotic Stabilization of the Prototypical Aeroelastic Wing Section via Tp Model Transformation

Bárányi

Köröndi

Hashimoto

2008

Asian Journal of Control

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A comprehensive analysis of aeroelastic systems has shown that these systems exhibit a broad class of pathological response regimes when certain types of non-linearities are included. In this paper, we propose a design method of a state-dependent non-linear controller for aeroelastic systems that includes polynomial structural non-linearities. The proposed method is based on recent numerical techniques such as the Tensor Product (TP) model transformation and the Linear Matrix Inequality (LMI) control design methods within the Parallel Distributed Compensation (PDC) frameworks. In order to link the TP model transformation and the LMI's in the proposed design method, we extend the TP model transformation with a further transformation. As an example, a controller is derived that ensures the global asymptotic stability of the prototypical aeroelastic wing section via one control surface, in contrast with previous approaches which have achieved local stability or applied additional control actuator on the purpose of achieving global stability. Numerical simulations are used to provide empirical validation of the control results. The effectiveness of the controller design is compared with a former approach.

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Chaotic motions of an airfoil with non-linear stiffness in incompressible flow

Cited by 133 publications

References 6 publications

Non-Linear System Identification for Aeroelastic Systems with Application to Experimental Data

Non-Linear System Identification for Aeroelastic Systems with Application to Experimental Data

Simple Questions for Interactive Information Retrieval

Global Asymptotic Stabilization of the Prototypical Aeroelastic Wing Section via Tp Model Transformation

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