NDLI: Design of decentralized supervisory based switching QFT controller for uncertain multivariable plants

Content Provider	IEEE Xplore Digital Library
Author	Namaki-Shoushtari, O. Sedigh, A.K.
Copyright Year	2009
Description	Author affiliation: Department of Electrical Engineering, K.N. Toosi University of Technology, P.O. Box 16315- 1355, Tehran, Iran (Namaki-Shoushtari, O.; Sedigh, A.K.)
Abstract	In this paper, design of decentralized switching control for uncertain multivariable plants based on the Quantitative Feedback Theory (QFT) is considered. In the proposed strategy, the uncertainty region is divided into smaller regions with a nominal model. It is assumed that a MIMO-QFT controller exists for robust stability and performance of the individual uncertain sets. The proposed control structure 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 makes the decision by comparing the local models behaviors with the one of the plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down switching to guarantee the overall closed loop stability. It is shown that this strategy provides a stable and robust adaptive controller to deal with complex multivariable plants with input-output pairing changes during the plant operation, which can facilitate the development of a reconfigurable decentralized control. Simulation results are employed to show the effectiveness of the proposed method.
Starting Page	934
Ending Page	939
File Size	578715
Page Count	6
File Format	PDF
ISBN	9781424438716
ISSN	01912216
DOI	10.1109/CDC.2009.5400221
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Uncertainty Adaptive control Robust control Stability Centralized control Least squares approximation Resonance light scattering Recursive estimation Process design Feedback loop
Content Type	Text
Resource Type	Article

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