Fuzzy Power Controller Design for Purdue University Research Reactor-1
Authors: Oktavian Muhammad Rizki, Appiah Rita, Lastres Oscar, Miller True, Chapman Alec, Tsoukalas Lefteri H.
Abstract:
The Purdue University Research Reactor-1 (PUR-1) is a 10 kWth pool-type research reactor located at Purdue University’s West Lafayette campus. The reactor was recently upgraded to use entirely digital instrumentation and control systems. However, currently, there is no automated control system to regulate the power in the reactor. We propose a fuzzy logic controller as a form of digital twin to complement the existing digital instrumentation system to monitor and stabilize power control using existing experimental data. This work assesses the feasibility of a power controller based on a Fuzzy Rule-Based System (FRBS) by modelling and simulation with a MATLAB algorithm. The controller uses power error and reactor period as inputs and generates reactivity insertion as output. The reactivity insertion is then converted to control rod height using a logistic function based on information from the recorded experimental reactor control rod data. To test the capability of the proposed fuzzy controller, a point-kinetic reactor model is utilized based on the actual PUR-1 operation conditions and a Monte Carlo N-Particle simulation result of the core to numerically compute the neutronics parameters of reactor behavior. The Point Kinetic Equation (PKE) was employed to model dynamic characteristics of the research reactor since it explains the interactions between the spatial and time varying input and output variables efficiently. The controller is demonstrated computationally using various cases: startup, power maneuver, and shutdown. From the test results, it can be proved that the implemented fuzzy controller can satisfactorily regulate the reactor power to follow demand power without compromising nuclear safety measures.
Keywords: Fuzzy logic controller, power controller, reactivity, research reactor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 433References:
[1] Zhengyu Huang, Kwang Y. Lee, and Robert M. Edwards, “Fuzzy Logic Control application in a nuclear power plant,” In: IFAC Proceedings Volumes 35.1, 2002, pp. 239–244.
[2] Tonatiuh Rivero-Gutierrez, Jorge S. Benıtez-Read, Armando Segovia-De-los-Rıos, Luis C. Longoria-Gandara and Javier C. Palacios-Hernandez, “Design and Implementation of a Fuzzy Controller for a TRIGA Mark III Reactor,” In:Science and Technology of Nuclear Installations, 2012, pp. 1-9.
[3] PUR-1information,https://engineering.purdue.edu/NE/research/ facilities/reactor/about-pur1, 2022.
[4] J. Armstrong, F.B. Brown, et. al., MCNP Users’ Manual Code Version 6.2 (Tech.). Los Alamos, New Mexico: Los Alamos National Laboratory, 2017.
[5] Ott, K, Introductory Nuclear Reactor Dynamics, ISBN: 0-89448- 029-4,1985.
[6] R. E. Uhrig, L. H. Tsoukalas and A. Ikonomopoulos, “Application of neural networks and fuzzy systems to power plants,” Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94), vol.6, pp. 3703-3718, 1994.
[7] D. Ruan, Fuzzy Systems and Soft Computing in Nuclear Engineering, Physica, New York, NY, USA, 2000.
[8] C.H. Townsend, Technical Specifications for the Purdue Reactor-1 Docket Number 50 -182. West Lafayette, IN 47907, 2016.
[9] J. R. Lamarsh, “Introduction to nuclear reactor theory”, Addison Wesley Publishing Company, INC, 1966.