Designing predictors for MIMO switching supervisory control

The paper studies the problem of inferring the behaviour of a linear feedback loop made up by an uncertain MIMO plant and a given candidate controller from data taken from the plant possibly driven by a different controller. In such a context, it is shown here that a convenient tool to work with is a quantity called normalized discrepancy. This is a measure of mismatch between the loop made up by the unknown plant in feedback with the candidate controller and the nominal ‘tuned-loop’ related to the same candidate controller. It is shown that discrepancy can in principle be obtained by resorting to the concept of a virtual reference, and conveniently computed in real time by suitably filtering an output prediction error. The latter result is of relevant practical value for on-line implementation and of paramount importance in switching supervisory control of uncertain plants, particularly in the case of a coarse distribution of candidate models. Copyright © 2001 John Wiley & Sons, Ltd.