Nonlinear identification of process dynamics using neural networks
- Texas A and M Univ., College Station, TX (United States). Dept. of Nuclear Engineering
- Univ. of California-Irvine, Dept. of Electrical and Computer Engineering, Irvine, CA (US)
In this paper the nonlinear identification of process dynamics encountered in nuclear power plant components is addressed, in an input-output sense, using artificial neural systems. A hybrid feedforward/feedback neural network, namely, a recurrent multilayer perceptron, is used as the model structure to be identified. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard backpropagation learning algorithm is modified, and it is used for the supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying process dynamics is investigated via the case study of a U-tube steam generator. The response of representative steam generator is predicted using a neural network, and it is compared to the response obtained from a sophisticated computer model based on first principles. The transient responses compare well, although further research is warranted to determine the predictive capabilities of these networks during more severe operational transients and accident scenarios.
- OSTI ID:
- 5776510
- Journal Information:
- Nuclear Technology; (United States), Vol. 97:1; ISSN 0029-5450
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
EXPERT SYSTEMS
NONLINEAR PROBLEMS
NUCLEAR POWER PLANTS
ALGORITHMS
ARTIFICIAL INTELLIGENCE
FEEDBACK
HYBRID COMPUTERS
MODIFICATIONS
REACTOR ACCIDENTS
TRANSIENTS
ACCIDENTS
COMPUTERS
MATHEMATICAL LOGIC
NUCLEAR FACILITIES
POWER PLANTS
THERMAL POWER PLANTS
220900* - Nuclear Reactor Technology- Reactor Safety
990200 - Mathematics & Computers