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In this paper, the problem of supervisory based switching Quantitative Feedback Theory (QFT) control is proposed for the control of highly uncertain plants. In the proposed strategy, the uncertainty region is divided into smaller regions with a nominal model. It is assumed that a QFT controller-prefilter exists for robust stability and performance of the smaller uncertainy subsets. The proposed control architecture is made up by these local controllers, which commute among themselves in accordance with the decision of a high level decision maker called the supervisor. The supervisor compares the candidate local model behaviors with the one of the real plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down switching for stability reasons. It is shown that this strategy improves closed loop performance, and can also handle the uncertainty sets that cannot be tackled by a single QFT robust controller. The multirealization technique to implement a family of controllers is employed to achieve bumpless transfer. Simulation results show the effectiveness of the proposed methodology.

Keywords: Switching Supervisory Adaptive Control, Robust Control, QFT, Bumpless Transfer.

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