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Discrete-time entropy formulation of optimal and adaptive control problemsThe discrete-time version of the entropy formulation of optimal control of problems developed by G. N. Saridis (1988) is discussed. Given a dynamical system, the uncertainty in the selection of the control is characterized by the probability distribution (density) function which maximizes the total entropy. The equivalence between the optimal control problem and the optimal entropy problem is established, and the total entropy is decomposed into a term associated with the certainty equivalent control law, the entropy of estimation, and the so-called equivocation of the active transmission of information from the controller to the estimator. This provides a useful framework for studying the certainty equivalent and adaptive control laws.
Document ID
19920073306
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Tsai, Yweting A.
(NASA Lewis Research Center Cleveland, OH, United States)
Casiello, Francisco A.
(NASA Lewis Research Center Cleveland, OH, United States)
Loparo, Kenneth A.
(Case Western Reserve University Cleveland, OH, United States)
Date Acquired
August 15, 2013
Publication Date
July 1, 1992
Publication Information
Publication: IEEE Transactions on Automatic Control
Volume: 37
Issue: 7 Ju
ISSN: 0018-9286
Subject Category
Cybernetics
Accession Number
92A55930
Funding Number(s)
CONTRACT_GRANT: NAG3-788
Distribution Limits
Public
Copyright
Other

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