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Optimal policies for identification of stochastic linear systemsThe problem of designing closed-loop policies for identification of multiinput-multioutput linear discrete-time systems with random time-varying parameters is considered in this paper using a Bayesian approach. A sensitivity index gives a measure of performance for the closed-loop laws. The computation of the optimal laws is shown to be nontrivial, an exercise in stochastic control, but open-loop, affine, and open-loop feedback optimal inputs are shown to yield tractable problems. Numerical examples are given. For time-invariant systems, the criterion considered is shown to be related to the trace of the information matrix associated with the system.
Document ID
19760033887
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Lopez-Toledo, A. A.
(Mexico, Universidad Autonoma Metropolitana, Mexico City, Mexico)
Athans, M.
(MIT Cambridge, Mass., United States)
Date Acquired
August 8, 2013
Publication Date
December 1, 1975
Publication Information
Publication: IEEE Transactions on Automatic Control
Volume: AC-20
Subject Category
Cybernetics
Accession Number
76A16853
Funding Number(s)
CONTRACT_GRANT: NSF GK-40493X
CONTRACT_GRANT: NGL-22-009-124
Distribution Limits
Public
Copyright
Other

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