Multiple‐model adaptive control using set‐valued observers

A multiple‐model adaptive control methodology is proposed that is able to provide stability and performance guarantees, for uncertain linear parameter‐varying plants. The identification problem is addressed by taking advantage of recent advances in model falsification using set‐valued observers (SVOs). These SVOs provide set‐valued estimates of the state of the system, according to its dynamic model. If such estimate is the empty set, the underlying dynamic model is invalidated, and a different controller is connected to the loop. The behavior of the proposed control algorithm is demonstrated in simulation, by resorting to a mass–spring–dashpot system. As a caveat, the computational burden associated with the SVOs can be prohibitive under some circumstances. Copyright © 2013 John Wiley & Sons, Ltd.