Flow separation control design with experimental validation

TL;DR

This paper compares two active feedback control strategies for flow separation, validating their effectiveness through wind tunnel experiments and providing practical design methods and a comprehensive dataset.

Contribution

It introduces and validates two flow separation control strategies—data-driven linear and phenomenological non-linear—offering practical design guidance and experimental validation.

Findings

Both control strategies effectively prevent flow separation.

The linear control is easier to tune, while the non-linear guarantees stability.

Experimental validation confirms the control methods' efficiency.

Abstract

Flow control aims at modifying a natural flow state to reach an other flow state considered as advantageous. In this paper, active feedback flow separation control is investigated with two different closed-loop control strategies, involving a reference signal tracking architecture. Firstly, a data-driven control law, leading to a linear (integral) controller is employed. Secondly, a phenomenological/model-driven approach, leading to a non-linear positive (integral) control strategy is investigated. While the former benefits of a tuning simplicity, the latter prevents undesirable effects and formally guarantees closed-loop stability. Both control approaches were validated through wind tunnel experiments of flow separation over a movable NACA 4412 plain flap. These control laws were designed with respect to hot film measurements, performed over the flap for different deflection angles. Both control approaches proved efficient in avoiding flow separation. The main contribution of this work is to provide practitioners simple but yet efficient ways to design a flow separation controller. In addition, a complete validation campaign data-set is provided.