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Subsystem‐level optimal control of weakly coupled linear stochastic systems composed of N subsystems
Author(s) -
Lim MyoTaeg,
Gajic Zoran
Publication year - 1999
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/(sici)1099-1514(199903/04)20:2<93::aid-oca648>3.0.co;2-g
Subject(s) - kalman filter , algebraic riccati equation , riccati equation , control theory (sociology) , transformation (genetics) , linear quadratic regulator , algebraic number , linear system , mathematics , optimal control , linear quadratic gaussian control , filter (signal processing) , stochastic control , computer science , control (management) , mathematical optimization , differential equation , mathematical analysis , biochemistry , statistics , chemistry , artificial intelligence , computer vision , gene
In this paper we introduce a transformation for the exact closed‐loop decomposition of the optimal control and Kalman filtering tasks of linear weakly coupled stochastic systems composed of N subsystems. In addition to having obtained N completely independent reduced‐order subsystem Kalman filters working in parallel, we have obtained the exact solution of the algebraic regulator and filter Riccati equations in terms of the solutions of the corresponding reduced‐order subsystem algebraic Riccati equations. The introduced transformation produces a lot of savings especially for on‐line computations since it allows parallel processing of information with lower‐order‐dimensional Kalman filters. The methodology presented is applied to a 17th‐order cold‐rolling mill. Copyright © 1999 John Wiley & Sons, Ltd.