Dealing with plant variations in multi-model unfalsified switching control via adaptive memory selection

In this paper, a multi-model unfalsified adaptive switching control scheme is proposed for controlling uncertain plants subject to time variations. In the adopted approach, the switching between the candidate controllers is orchestrated according to a hysteresis logic variant wherein the memory length is adaptively selected, on the basis of the exhibited plant I/O behavior, so that past recorded data can be safely discarded. To this end, novel model-based resetting conditions are introduced. The global stability of the resulting switched closed-loop system is guaranteed provided that, at every time instant, a stabilizing candidate controller exists and that the (possibly abrupt) changes in the plant model are infrequent.