  A novel, model free, approach to experimental closed-loop flow control is
implemented on a separated flow. Feedback control laws are generated using
genetic programming where they are optimized using replication, mutation and
cross-over of best performing laws to produce a new generation of candidate
control laws. This optimization process is applied automatically to a
backward-facing step flow at Re=1350, controlled by a slotted jet, yielding an
effective control law. Convergence criterion are suggested. The law is able to
produce effective action even with major changes in the flow state,
demonstrating its robustness. The underlying physical mechanisms leveraged by
the law are analyzed and discussed. Contrary to traditional periodic forcing of
the shear layer, this new control law plays on the physics of the recirculation
area downstream the step. While both control actions are fundamentally
different they still achieve the same level of effectiveness. Furthermore the
new law is also potentially easier and cheaper to implement actuator wise.
