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Implementations of learning control systems using neural networksThe systematic storage in neural networks of prior information to be used in the design of various control subsystems is investigated. Assuming that the prior information is available in a certain form (namely, input/output data points and specifications between the data points), a particular neural network and a corresponding parameter design method are introduced. The proposed neural network addresses the issue of effectively using prior information in the areas of dynamical system (plant and controller) modeling, fault detection and identification, information extraction, and control law scheduling.
Document ID
19920050991
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Sartori, Michael A.
(U.S. Navy, David W. Taylor Naval Ship Research and Development Center Bethesda, MD, United States)
Antsaklis, Panos J.
(Notre Dame, University IN, United States)
Date Acquired
August 15, 2013
Publication Date
April 1, 1992
Publication Information
Publication: IEEE Control Systems Magazine
Volume: 12
ISSN: 0272-1708
Subject Category
Cybernetics
Accession Number
92A33615
Funding Number(s)
CONTRACT_GRANT: JPL-957856
Distribution Limits
Public
Copyright
Other

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