Controlling Neutron Power of a TRIGA Mark III Research Nuclear Reactor with Fuzzy Adaptation of the Set of Output Membership Functions

  • Jorge S. Benítez-Read
  • Daniel Vélez-Díaz
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 38)


A fuzzy method is developed to obtain the set of output membership functions (SOMF) to be used in the defuzzification process of a typical fuzzy rule based control system. The universe, domain, and distribution of the controller’s output membership functions are defined at the beginning of every control cycle, thus having a dynamic generation of the SOMF. One or more relevant parameters of the controlled process are used as inputs to the SOMF fuzzy adaptation stage. The fuzzy method designed is incorporated into a fuzzy control algorithm applied to a point-kinetic model of a TRIGA Mark III research nuclear reactor. The control objective is to take the neutron power from its source level up to a desired setpoint, avoiding undesirable power excursions, specially at low power levels, in order to maintain the reactor period above the pre-specified lower limit during power ascent. Likewise, once the desired power level is attained in a soft manner, the fuzzy controller should act as a regulator of the power level for long periods of time. Simulation results are analysed and compared with the response provided by a fuzzy controller without SOMF adaptation. A general conclusion drawn from the better performance obtained with adaptation is that knowledge of the dynamic characteristics of the controlled system may be used to provide some kind of knowledge-based adjustment of the controller’s parameters to improve the response of the closed-loop system.


Membership Function Nuclear Power Plant Fuzzy Rule Fuzzy Controller Output Membership Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Benitez-Read JS, Jamshidi M, Kisner R (1992), “Advanced Control Designs for Nuclear Reactors,” Control —Theory and Advanced Technology, C—TAT, vol 8, (3), pp 447–464, September.Google Scholar
  2. Benitez-Read JS, Jamshidi M (1992), “Adaptive Input-ouput Linearizing Control of Nuclear Reactors,” Control —Theory and Advanced Technology, C —TAT, vol 8, (3), pp 525–546, September.Google Scholar
  3. Benitez-Read JS, Abdallah C, Kumbla KK (1994), “Adaptive Nonlinear Control for Neutron Power Tracking in a Research Reactor,” Proc. of the European Simulation Symposium, vol II, pp 195–199.Google Scholar
  4. Benitez-Read JS, Vélez-Diaz D (1996), “Neutron Power Control in a Research Reactor Using a Fuzzy Rule Based System,” Soft Computing with Industrial Applications, vol 5, pp 53–58, TSI Press Series.Google Scholar
  5. Benitez-Read JS, Vélez-Díaz D (1998), “Comparative Study of Fuzzy Control Algorithms for a Nuclear Reactor,” Intelligent Automation and Soft Computing, vol 1, pp ISORA-023.1–6, TSI Press CD ROMS Series.Google Scholar
  6. Bereznai GT (1973), “Adaptive Nuclear Reactor Control Based on Optimal Low-Order Linear Models,” IEEE Transaction on Nuclear Science, April, vol NS-20, 2, pp 72–79.Google Scholar
  7. Bernard JA, Lanning DD, Ray A (1984), “Digital Control of Power Transients in a Nuclear Reactor,” IEEE Transaction on Nuclear Science, February, vol. NS-31, (1), pp 701–705.Google Scholar
  8. Bernard JA (1986), “The Construction and Use of a Knowledge Base in the Real-Time Control of Research Reactor Power,” Proceedings of the Sixth Power Plant Dynamics, Control and Testing Symposium, Knoxville, TN, April.Google Scholar
  9. Bernard JA (1988), “Evaluation of ‘Period-Generated’ Control Laws for the Time-Optimal Control of Reactor Power,” IEEE Transaction on Nuclear Science, February, vol NS-35, (1), pp 888–893.Google Scholar
  10. Bubak M, Moscinski J (1983), “A Fuzzy-Logic Approach to HTR Nuclear Power Plant Model Control,” Annals of Nuclear Energy UK, vol 10, (9), pp 467–471.CrossRefGoogle Scholar
  11. DeGroot MN (1968), “TRIGA Mark III Reactor: Instrumentation Maintenance Handbook,” Document No. GA-8585, Gulf General Atomic, Inc.Google Scholar
  12. Edwards RM, Garcia HE, Turso JA, Chavez CM, Abdennour AB, Weng CK, Ku CC, Ray A, Lee KY (1992), “Advanced Control Research at the Pennsylvania State University,” Advanced digital computers, controls, and automation technologies for power plants: Proceedings, Electric Power Research Inst., Palo Alto, CA (United States), August, pp 26. 1–26. 10.Google Scholar
  13. Hetrick DL (1971), Dynamics of Nuclear Reactors. The University of Chicago Press.Google Scholar
  14. Jungin C, Yungjoon H, Unchul L (1993), “Automatic Reactor Power Control for a Pressurized Water Reactor,” Nuclear Technology, May, vol 102, (2), pp 277–286.Google Scholar
  15. Leopando LS (1998), “Incorporation of Personal Computers in a Research Reactor Instrumentation System for Data Monitoring and Analysis,” Proc. of an IAEA Final Research Co-ordination Meeting, February, pp 97–115.Google Scholar
  16. Lin C, Lee C, Raghavan R, Fahrner DM (1995), “Fuzzy Logic Control of Water Level in Advanced Boiling Water Reactor,” Proc. of the International Conference on Mathematics and Computations, Reactor Physics, and Environmental Analyses, Portland, OR, USA, 30 Apr - 4 May 1995, vol 1–2, pp 32–38; La Grange Park, IL, USA, American Nuclear Society, Inc. 1995.Google Scholar
  17. Lipinski WC, Vacroux AG (1970), “Optimal Digital Computer Control of Nuclear Reactor,” IEEE Transaction on Nuclear Science, February, vol NS-17, (1), pp 510516.Google Scholar
  18. Moon BS (1993), “Fuzzy Logic Controllers for the Nuclear Power Plants: Simulation Experiences,” Hungarian Korean Symposium on Nuclear Energy, Balatonfuered (Hungary), 30 Mar–2 Apr 1993, Uri,-G. (ed), Nuclear Energy, Budapest, Hungary, pp 237–250.Google Scholar
  19. Nah MK (1995), “Application of Adaptive Control Theory to Nuclear Reactor Power Control,” Journal of the Korean Nuclear Society, June, vol 27, (3), pp 336–343.Google Scholar
  20. Nava W (1991), “Automatic Operation in Stationary Mode,” (In Spanish), Instruction: I. UR-10, Rev 2, May 17, Instituto Nacional de Investigaciones Nucleares (ININ), México.Google Scholar
  21. Pérez-Carbajal V (1994), Input-Output Linearizing Control of a Nuclear Reactor, (In Spanish), BSc Thesis, May 1994, Instituto Tecnologico de Toluca, México.Google Scholar
  22. Raju GVS, Fadra UG (1973), “Design of an Optimal Noninteracting Control System,” IEEE Transaction on Nuclear Science, February, vol NS-20, (1), pp 668–674.Google Scholar
  23. Saif M (1989), “A Novel Approach for Optimal Control of a Pressurized Water Reactor,” IEEE Transaction on Nuclear Science, February, vol NS-36, (1), pp 1317–1325.Google Scholar
  24. Shibuya S, Iijima T (1996), “Application of Fuzzy Logic Control System for Reactor Feedwater Control,” Advances in the Operational Safety of Nuclear Power Plants, Proceedings of an International Symposium, pp 601, International Atomic Energy Agency, Vienna (Austria).Google Scholar
  25. Silvinsky CR, Schultz DG (1970), “State Variable Feedback and Series Compensator of Multivariable System,” Nuclear Science Engineering, vol 41, (1), pp 125–129.Google Scholar
  26. Sun BKH (1997), “Control and Automation Technology in United States Nuclear Power Plants,” Advanced control systems to improve nuclear power plant reliability and efficiency. international, July, pp 177–184, Atomic Energy Agency, Vienna (Austria).Google Scholar
  27. Takahashi Y, Takamatsu S (1965), “Digital Start-Up Control of a Research Reactor”, IEEE Transaction on Nuclear Science, August, vol NS-12, (4), pp 355–366.Google Scholar
  28. Tepper L (1975), “Suboptimal Control Study of a Nuclear Power Plant,” IEEE Transaction on Nuclear Science, February, vol NS-22, (1), pp 812–819.Google Scholar
  29. Vélez-Díaz D, Benitez-Read JS (1995), “Study of the Behavior of a TRIGA Reactor Point Kinetic Model, Based on Simulations,” (In Spanish), Technical report IT.ET.A- 9514, Instituto Nacional de Investigaciones Nucleares, México.Google Scholar
  30. Vélez–Diaz D, Benitez–Read JS (1997), “Fuzzy System to Control the Neutron Power with Different Sets of Output Membership Functions,” Proc. 7th IFSA World Congress, vol IV, pp 132–136, ISBN 80–200–0633–8, Prague, Czech Republic, June 25 – 29.Google Scholar
  31. Weaver LE, Vanesse RE (1967), “State Variable Feedback Control of Multiregion Reactors,” Nuclear Science and Engineering, vol 29, pp 264–271.MATHGoogle Scholar
  32. Weng CK, Edwards RM, Ray A (1994) “Robust Wide-Range Control of Nuclear Reactors by Using the Feedforward-Feedback Concept,” Nuclear Science and Engineering, July, vol 117, (3), pp 177–185.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Jorge S. Benítez-Read
    • 1
  • Daniel Vélez-Díaz
    • 1
  1. 1.Instituto Nacional de Investigaciones NuclearesGerencia de Ciencias AplicadasCol. EscandónMéxico, D.F.

Personalised recommendations