NDLI: A neural network controller for load following operation of nuclear reactors

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A neural network controller for load following operation of nuclear reactors

Content Provider	IEEE Xplore Digital Library
Author	Khajavi, M.N. Menhaj, M.B. Suratgar, A.A.
Copyright Year	2001
Description	Author affiliation: Phys. Dept., Amir-Kabir Univ. of Technol., Tehran, Iran (Khajavi, M.N.)
Abstract	Nuclear reactors are in nature nonlinear and their parameters vary with time as a function of power level, fuel burn-up, and control rod worth. Therefore, these characteristics must be considered if large power variations occur in power plant working regimes (for example in load following conditions). In this paper a neural network controller (NNC) is presented. A robust optimal self-tuning regulator (ROSTR) response is used as a reference trajectory to determine the feedback, feedforward and observer gains of the NNC. The NNC displays good stability and performance for a wide range of operation as well as considerable reduction in computation time with regard to the ROSTR and fuzzy logic controller (FAROC).
Sponsorship	Int. Neural Network Soc.
Starting Page	491
Ending Page	496
File Size	345861
Page Count	6
File Format	PDF
ISBN	0780370449
ISSN	10987576
DOI	10.1109/IJCNN.2001.939069
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-07-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Fission reactors Fuels Power generation Robustness Adaptive control Neurofeedback Stability Computer displays Fuzzy logic
Content Type	Text
Resource Type	Article

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