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Generalized Kleinman‐Newton method
Author(s) -
Geromel José C.,
Deaecto Grace S.
Publication year - 2018
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/oca.2400
Subject(s) - generalization , monotone polygon , mathematics , convergence (economics) , mathematical optimization , algebraic riccati equation , optimal control , control (management) , regular polygon , computer science , control theory (sociology) , riccati equation , differential equation , mathematical analysis , geometry , artificial intelligence , economics , economic growth
Summary This paper addresses the general problem of optimal linear control design subject to convex gain constraints. Classical approaches based exclusively on Riccati equations or linear matrix inequalities are unable to treat problems that incorporate feedback gain constraints, for instance, the reduced‐order (including static) output feedback control design. In this paper, these two approaches are put together to obtain a genuine generalization of the celebrated Kleinman‐Newton method. The convergence to a local minimum is monotone. We believe that other control design problems can be also considered by the adoption of the same ideas and algebraic manipulations. Several examples borrowed from the literature are solved for illustration and comparison.