Closed-Loop Turbulence Control: Progress and Challenges

2015/07/30 by Steven L. Brunton, Bernd R. Noack · 623 citations
Engineering · Physics and Astronomy · #Adaptive control #Aerodynamics #Aerodynamics and Acoustics in Jet Flows #Aerospace engineering #Artificial intelligence #Computer science #Control (management) #Control engineering #Control theory (sociology) #Drag #Engineering #Fluid Dynamics and Turbulent Flows #Model Reduction and Neural Networks #Nonlinear system #Physics #Turbulence

paper · doi:10.1115/1.4031175

published in Applied Mechanics Reviews 67(5) (American Society of Mechanical Engineers)

openalex publication_date 2015/07/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Closed-loop turbulence control is a critical enabler of aerodynamic drag reduction, lift increase, mixing enhancement, and noise reduction. Current and future applications have epic proportion: cars, trucks, trains, airplanes, wind turbines, medical devices, combustion, chemical reactors, just to name a few. Methods to adaptively adjust open-loop parameters are continually improving toward shorter response times. However, control design for in-time response is challenged by strong nonlinearity, high-dimensionality, and time-delays. Recent advances in the field of model identification and system reduction, coupled with advances in control theory (robust, adaptive, and nonlinear) are driving significant progress in adaptive and in-time closed-loop control of fluid turbulence. In this review, we provide an overview of critical theoretical developments, highlighted by compelling experimental success stories. We also point to challenging open problems and propose potentially disruptive technologies of machine learning and compressive sensing.

Citations

• Stability of extremum seeking feedback for general nonlinear dynamic systems
• Balanced Model Reduction via the Proper Orthogonal Decomposition
• The Homogeneous Chaos

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