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Identification for decentralized model predictive control
Author(s) -
Gudi Ravindra D.,
Rawlings James B.
Publication year - 2006
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.10781
Subject(s) - identification (biology) , a priori and a posteriori , controller (irrigation) , scheme (mathematics) , model predictive control , software deployment , control engineering , decentralised system , computer science , system identification , control (management) , identification scheme , control theory (sociology) , engineering , data mining , artificial intelligence , mathematics , mathematical analysis , philosophy , botany , epistemology , agronomy , biology , measure (data warehouse) , operating system
The problem of identifying interaction dynamics that exist between units operating in a decentralized control scheme is addressed. Identification of such interaction relationships is crucial to the deployment of coordinated decentralized control. The proposed methodology is based on a variant of the two‐step, closed‐loop identification methods proposed earlier in the literature. Alternative identification schemes relevant for this scenario are theoretically analyzed and are also evaluated based on the criteria of a priori knowledge necessary about the controller and the plant, as well as the applicability of the methods for the constrained controller case. Validation studies on representative systems taken from literature are presented to demonstrate the efficacy of the proposed schemes. © 2006 American Institute of Chemical Engineers AIChE J, 2006