Data-Driven Controller Unfalsification With Analytic Update Applied to a Motion System

Ellipsoidal unfalsified control is a plant-model-free, data-driven control design method. It recursively checks, using available data, whether the ability of a controller to meet a predefined performance requirement is (un)falsified. The set of unfalsified controllers is described by an ellipsoid in the control parameter space. The update of the ellipsoid employing new measurements can be computed analytically, hence, it is computationally cheap. This adaptive scheme is applied to an experimental motion system, namely to an industrial inkjet printer at a sample rate of 1 kHz. The results clearly show that the algorithm updates the control parameter set when the performance requirement is not met with the currently implemented one. The resulting closed-loop behavior resembles the predefined reference model in the dominant frequency range.