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Associative stochastic automaton for reactor power ascent

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4 Author(s)
Jouse, W.C. ; Dept. of Nucl. Eng., Arizona Univ., Tucson, AZ, USA ; Bin Shen ; Xiao Xu ; Williams, J.G.

The dynamics of experimental nuclear reactors exhibit strong non-linearities, while the constraints associated with their operation embody a number of safety-related decision points and protective trips. For power maneuvering, existing control technologies include human operators, state variable feedback controllers, and digital model-based controllers. In this work, we demonstrate the use of an associative stochastic automaton as an alternative. Factors which lead to the success of the application are discussed

Published in:
Nuclear Science, IEEE Transactions on  (Volume:41 ,  Issue: 4 )

Date of Publication: Aug 1994

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