Sparse reduced-order modeling of the fluidic pinball
Résumé
This work applies a sparse gray-box modeling procedure recently proposed by the same authors to the fluidic
pinball, a new benchmark for nonlinear flow control. This procedure relies on experimentally available quantities,
such as time-resolved sensor measurements and optional non-time-resolved PIV snapshots. Its application to the
fluidic pinball illustrates the versatility of the present approach and its ability to identify human-interpretable
nonlinear low-order models. These low-order models may then be used for nonlinear model-based control.