Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/106968
Type: Artigo de periódico
Title: Constrained Robust Predictive Controller For Uncertain Processes Modeled By Orthonormal Series Functions
Author: Oliveira G.H.C.
Amaral W.C.
Favier G.
Dumont G.A.
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.
Editor: Elsevier Science Ltd, Exeter, United Kingdom
Rights: fechado
Identifier DOI: 10.1016/S0005-1098(99)00179-X
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-0033874692&partnerID=40&md5=642bfc5c435d4f844e57b7d1936fe743
Date Issue: 2000
Appears in Collections:Unicamp - Artigos e Outros Documentos

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