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Research Papers

Damage-Mitigating Predictive Control of Airfoil Flutter for a General Hypersonic Flight Vehicle

[+] Author and Article Information
Xiaohui Zhang

College of Automation Engineering,
Nanjing University of Aeronautics and Astronautics,
Nanjing 211106, China
e-mail: zhangxiaoh@nuaa.edu.cn

Yuhui Wang

College of Automation Engineering,
Nanjing University of Aeronautics and Astronautics,
Nanjing 211106, China
e-mail: wangyh@nuaa.edu.cn

Xingkai Feng

College of Automation Engineering,
Nanjing University of Aeronautics and Astronautics,
Nanjing 211106, China
e-mail: fengstar@nuaa.edu.cn

Siyuan Hou

College of Automation Engineering,
Nanjing University of Aeronautics and Astronautics,
Nanjing 211106, China
e-mail: housiyuan@nuaa.edu.cn

1Corresponding author.

Contributed by the Technical Committee on Vibration and Sound of ASME for publication in the Journal of Vibration and Acoustics. Manuscript received August 1, 2018; final manuscript received April 10, 2019; published online June 5, 2019. Assoc. Editor: Alper Erturk.

J. Vib. Acoust 141(5), 051007 (Jun 05, 2019) (9 pages) Paper No: VIB-18-1323; doi: 10.1115/1.4043511 History: Received August 01, 2018; Accepted April 10, 2019

This paper aims to investigate the airfoil flutter damage-mitigating problem in hypersonic flow. A new adaptive robust nonlinear predictive control law is designed in this paper to mitigate the damage during airfoil flutter of a generic hypersonic flight vehicle. A three-degrees-of-freedom airfoil dynamic motion model is established, in which the third piston theory is employed to derive the unsteady aerodynamics. Then, the complicated responses of the hypersonic airfoil flutter model are analyzed. In order to mitigate the damage of the airfoil, a predictive controller is designed by introducing an adaptive predictive period, and asymptotical stability analysis of the robust nonlinear predictive controller is performed. Subsequently, based on the nonlinear aerodynamics of the airfoil and damage accumulation model, the damage of the airfoil is observed online. Simulation results illustrate the effectiveness of the proposed method.

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Figures

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Fig. 1

Three degrees-of-freedom airfoil motion system

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Fig. 2

Flutter responses and damage evolution at V1 = 14.3000: (a) pitching displacement response, (b) phase diagram response, and (c) damage evolution

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Fig. 3

Flutter responses and damage evolution at V1 = 19.5883: (a) pitching displacement response, (b) phase diagram response, and (c) damage evolution

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Fig. 4

Flutter responses and damage evolution at V1 = 21.0000: (a) pitching displacement response, (b) phase diagram response, and (c) damage evolution

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Fig. 5

Diagram of the predictive period

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Fig. 6

Flutter responses and damage evolution under the control at V = 19.5883: (a) pitching displacement responses, (b) phase diagram responses, and (c) damage evolution

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Fig. 7

Flutter responses and damage evolution under the control at V = 21.0000: (a) pitching displacement responses, (b) phase diagram responses, and (c) damage evolution

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Fig. 8

Flutter responses under different predictive period parameters at V = 21.0000: (a) = −104 and (b) = 200, = 60

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