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Transonic buffet flow adaptive control with time-variant reduced-order model

Published online by Cambridge University Press:  03 November 2025

Chuanqiang Gao Open the ORCID record for Chuanqiang Gao [Opens in a new window] ,
Xinyu Yang Open the ORCID record for Xinyu Yang [Opens in a new window] ,
Kai Ren Open the ORCID record for Kai Ren [Opens in a new window]  and
Weiwei Zhang Open the ORCID record for Weiwei Zhang [Opens in a new window]
Chuanqiang Gao
Affiliation:
School of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, PR China International Joint Institute of Artificial Intelligence on Fluid Mechanics, Northwestern Polytechnical University, Xi’an 710072, PR China National Key Laboratory of Aircraft Configuration Design, Xi’an 710072, PR China
Xinyu Yang
Affiliation:
School of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, PR China International Joint Institute of Artificial Intelligence on Fluid Mechanics, Northwestern Polytechnical University, Xi’an 710072, PR China National Key Laboratory of Aircraft Configuration Design, Xi’an 710072, PR China
Kai Ren
Affiliation:
School of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, PR China International Joint Institute of Artificial Intelligence on Fluid Mechanics, Northwestern Polytechnical University, Xi’an 710072, PR China National Key Laboratory of Aircraft Configuration Design, Xi’an 710072, PR China
Weiwei Zhang*
Affiliation:
School of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, PR China International Joint Institute of Artificial Intelligence on Fluid Mechanics, Northwestern Polytechnical University, Xi’an 710072, PR China National Key Laboratory of Aircraft Configuration Design, Xi’an 710072, PR China
*
Corresponding author: Weiwei Zhang, aeroelastic@nwpu.edu.cn
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Abstract

Transonic buffet is a complex and strongly nonlinear unstable flow sensitive to variations in the incoming flow state. This poses great challenges for establishing accurate-enough reduced-order models, limiting the application of model-based control strategies in transonic buffet control problems. To address these challenges, this paper presents a time-variant modelling approach that incorporates rolling sampling, recursive parameter updating and inner iteration strategies under dynamic incoming flow conditions. The results demonstrate that this method successfully overcomes the difficulty in designing appropriate training signals and obtaining unstable steady base flow. Additionally, it improves the global predictive capability and identification efficiency of linear models for nonlinear flow-system responses by more than one order of magnitude. Furthermore, two adaptive control strategies – minimum variance control and generalised predictive control – are validated as effective based on the time-variant reduced-order model through numerical simulations of the transonic buffet flow over the NACA 0012 aerofoil. The adaptive controllers effectively regulate the unstable eigenvalues of the flow system, achieving the desired control outcomes. They ensure that the shock wave buffet phenomenon does not recur after control is applied, and that the actuator deflection, specifically the trailing-edge flap, returns to zero. Moreover, the control results further confirm the global instability essence of transonic buffet flow from a control perspective, thereby deepening the cognition of this nonlinear unstable flow.

JFM classification

Nonlinear Dynamical Systems: Low-dimensional models Flow Control: Control theory Wakes/Jets: Separated flows

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Type
JFM Papers
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Journal of Fluid Mechanics , Volume 1022 , 10 November 2025 , A32
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© The Author(s), 2025. Published by Cambridge University Press

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