DocumentCode :
2476310
Title :
Spectral factorization of non-classical information structures under feedback
Author :
Swigart, John ; Lall, Sanjay
Author_Institution :
Dept. of Aeronaut. & Astronaut., Stanford Univ., Stanford, CA, USA
fYear :
2009
fDate :
10-12 June 2009
Firstpage :
457
Lastpage :
462
Abstract :
We consider linear systems under feedback. We restrict our attention to non-classical information structures for which the optimal control policies can be found via a convex optimization problem. The first step to analytically solving such control problems is performing a spectral factorization to solve the optimality condition. In this paper we discuss two classes of information structures, for which such spectral factorizations can be found. In the first structure, the only constraint is that the controller can remember previous inputs that it has received. In the second structure, we consider a controller which is allowed to forget previous observations.
Keywords :
convex programming; linear systems; optimal control; convex optimization problem; linear system; nonclassical information structure; optimal control; spectral factorization; Centralized control; Control systems; Cost function; Distributed control; Gaussian noise; Linear feedback control systems; Linear systems; Optimal control; Performance analysis; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2009. ACC '09.
Conference_Location :
St. Louis, MO
ISSN :
0743-1619
Print_ISBN :
978-1-4244-4523-3
Electronic_ISBN :
0743-1619
Type :
conf
DOI :
10.1109/ACC.2009.5160614
Filename :
5160614
Link To Document :
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