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Fuzzy and neural controlFuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.
Document ID
19940017797
Acquisition Source
Legacy CDMS
Document Type
Technical Memorandum (TM)
Authors
Berenji, Hamid R.
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
September 6, 2013
Publication Date
May 1, 1992
Subject Category
Cybernetics
Report/Patent Number
NASA-TM-108753
FIA-92-19
NAS 1.15:108753
Report Number: NASA-TM-108753
Report Number: FIA-92-19
Report Number: NAS 1.15:108753
Accession Number
94N22270
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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