Publications Details

Direct optimal controller identification for uncertain systems using frequency response function data

Holzel, Matthew; Lacy, Seth; Babuska, Vit

Here we present a new approach to optimal controller identification which unifies system identification and optimal control theory. Starting with empirical, open-loop frequency response function (FRF) data from a system, it is shown that the optimal controller can be identified directly without performing the intermediary steps of system identification and controller design. The primary benefit is that we are able to work directly with the measured data and the uncertainties inherent in it. Further, we go on to show a method of incorporating the empirical FRF uncertainty into the cost for robustness against plant uncertainty. This method leads to a more precise identification of H 2 and LQG controllers since it avoids the residual errors associated with performing the traditional intermediary step of system identification, while concurrently accounting for measured system uncertainty. © 2009 IFAC.