Tuned l1 identification from impulse response data: application to a fluid dynamics problem

Three tuned, convergent identification algorithms which compute a model and an l₁ error bound from the impulse response experimental data, are presented. Two are tuned to the measurement noise bound, which in practical cases, is well known. The third one is asymptotically optimal and is tuned to the a priori information on both, the system and the noise. These procedures are applied to the identification of a Taylor-Couette hydrodynamic instability process, which is essentially an infinite dimensional problem.