Constrained robust predictive controller for uncertain processes modeled by orthonormal series functions

TitleConstrained robust predictive controller for uncertain processes modeled by orthonormal series functions
Publication TypeJournal Article
Year of Publication2000
AuthorsOliveira, G. H. C., W. C. Amaral, G. Favier, and G. A. Dumont
JournalAutomaticA
Volume36
Pagination563-571
Date PublishedAPR
Type of ArticleProceedings Paper
ISSN0005-1098
Keywordsorthonormal series functions, predictive control, robust control, uncertain dynamic systems
Abstract

The present work focuses on robust predictive control (RPC) of uncertain processes and proposes a new approach based on orthonormal series function modeling. In such unstructured modeling, the output signal is described as a weighted sum of orthonormal functions that uses approximative information about the time constant of the process. Due to an efficient uncertainty representation, this kind of modeling is advantageous in the RPC context, even for constrained systems and processes with integral action. The stability of the closed-loop system is guaranteed by the setting of sufficient conditions for the selection of the controller prediction horizon. Simulation results are presented to illustrate the performance of this new RPC algorithm. (C) 2000 Elsevier Science Ltd. All rights reserved.

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