- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Journal of Engineering
Volume 2013 (2013), Article ID 450161, 12 pages
Analysis of Liquid Zone Control Valve Oscillation Problem in CANDU Reactors
University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, ON, Canada L1H 7K4
Received 14 November 2012; Revised 15 March 2013; Accepted 2 April 2013
Academic Editor: Ibrahim Asi
Copyright © 2013 Elnara Nasimi and Hossam A. Gabbar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- J. G. Williams and W. C. Jouse, “Intelligent control in safety systems: criteria for acceptance in the nuclear power industry,” IEEE Transactions on Nuclear Science, vol. 40, no. 6, pp. 2040–2044, 1993.
- D. E. Goldberg, Genetic Algorithms in Search Optimizations and Machine Learning, Addison-Wesley, Reading, Mass, USA, 1989.
- Y. Zhang and J. Jiang, “Bibliographical review on reconfigurable fault-tolerant control systems,” Annual Reviews in Control, vol. 32, no. 2, pp. 229–252, 2008.
- H. E. Rauch, “Intelligent fault diagnosis and control reconfiguration,” IEEE Control Systems, vol. 14, no. 3, pp. 6–12, 1994.
- M. Bruccoleri, M. Amico, and G. Perrone, “Distributed intelligent control of exceptions in reconfigurable manufacturing systems,” International Journal of Production Research, vol. 41, no. 7, pp. 1393–1412, 2003.
- M. G. Mehrabi, A. G. Ulsoy, Y. Koren, and P. Heytler, “Trends and perspectives in flexible and reconfigurable manufacturing systems,” Journal of Intelligent Manufacturing, vol. 13, no. 2, pp. 135–146, 2002.
- “INL—Idaho National Laboratory,” https://inlportal.inl.gov/portal/server.pt/community/instrumentation,_control_and_intelligent_systems/315/dcnf.
- M. Boroushakia, M. B. Ghofrania, C. Lucasb, and M. J. Yazdanpanahb, “An intelligent nuclear reactor core controller for load following operations, using recurrent neural networks and fuzzy systems,” Annals of Nuclear Energy, vol. 30, no. 1, pp. 63–80, 2003.
- M. Boroushakia, M. B. Ghofrania, C. Lucasb, M. J. Yazdanpanahb, and N. Sadatic, “Axial offset control of PWR nuclear reactor core using intelligent techniques,” Nuclear Engineering and Design, vol. 227, no. 3, pp. 285–300, 2004.
- S. S. Khorramabadi, M. Boroushaki, and C. Lucas, “Emotional learning based intelligent controller for a PWR nuclear reactor core during load following operation,” Annals of Nuclear Energy, vol. 35, no. 11, pp. 2051–2058, 2008.
- M. Boroushaki, M. B. Ghofrani, C. Lucas, and M. J. Yazdanpanah, “Identification and control of a nuclear reactor core (VVER) using recurrent neural networks and fuzzy systems,” IEEE Transactions on Nuclear Science, vol. 50, no. 2, pp. 159–174, 2003.
- D. Ruan, “Intelligent systems in nuclear applications,” International Journal of Intelligent Systems, vol. 13, pp. 115–125, 1998.
- R. S. Gilbert, “Control and safety computers in CANDU power stations,” in Nuclear Power and Electronics, IAEA Bulletin, 1985, http://www.iaea.org/Publications/Magazines/Bulletin/Bull273/27302390712.pdf.
- S. J. Qina and T. A. Badgwell, “Survey of industrial model predictive control technology,” Control Engineering Practice, vol. 11, pp. 733–764, 2003, http://www.elsevier.com/.
- K. Hu and J. Yuan, “Multi-model predictive control method for nuclear steam generator water level,” Energy Conversion and Management, vol. 49, no. 5, pp. 1167–1174, 2008, http://www.sciencedirect.com/.
- M. G. Na, “Auto-tuned PID controller using a model predictive control method for the steam generator water level,” IEEE Transactions on Nuclear Science, vol. 48, no. 5, pp. 1664–11671, 2001.
- G. Xia, J. Su, and W. Zhang, “Multivariable integrated model predictive control of nuclear power plant,” in Proceedings of the 2nd International Conference on Future Generation Communication and Networking Symposia (FGCNS '08), pp. 8–11, December 2008.
- M. G. Na and I. J. Hwang, “Design of a PWR power controller using model predictive control optimized by a genetic algorithm,” Nuclear Engineering and Technology, vol. 38, no. 1, 2006, http://www.kns.org/jknsfile/v38/JK0380081.pdf.