Neural network setpoint control of an advanced test reactor experiment loop simulation [electronic resource].
- Washington, D.C. : United States. Office of the Assistant Secretary for Nuclear Energy, 1990. and Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
- Physical Description:
- Pages: (63 pages) : digital, PDF file
- Additional Creators:
- United States. Office of the Assistant Secretary for Nuclear Energy and United States. Department of Energy. Office of Scientific and Technical Information
- This report describes the design, implementation, and application of artificial neural networks to achieve temperature and flow rate control for a simulation of a typical experiment loop in the Advanced Test Reactor (ATR) located at the Idaho National Engineering Laboratory (INEL). The goal of the project was to research multivariate, nonlinear control using neural networks. A loop simulation code was adapted for the project and used to create a training set and test the neural network controller for comparison with the existing loop controllers. The results for three neural network designs are documented and compared with existing loop controller action. The neural network was shown to be as accurate at loop control as the classical controllers in the operating region represented by the training set. 9 refs., 28 figs., 2 tabs.
- Published through SciTech Connect., 09/01/1990., "egg-ee-8935", "DE91001844", Powell, R.H.; Bryan, S.R.; Cordes, G.A.; Chick, D.R., and EG and G Idaho, Inc., Idaho Falls, ID (USA)
- Funding Information:
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