[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.14248/JKOSSE.2018.14.2.058

A Systematic Engineering Approach to Design the Controller of the Advanced Power Reactor 1400 Feedwater Control System using a Genetic Algorithm

Tran, Thanh Cong (IKEPCO International Nuclear Graduate School)
Jung, Jae Cheon (IKEPCO International Nuclear Graduate School)

Publication Information

Journal of the Korean Society of Systems Engineering / v.14, no.2, 2018 , pp. 58-66 More about this Journal

Abstract

This paper represents a systematic approach aimed at improving the performance of the proportional integral (PI) controller for the Advanced Power Reactor (APR) 1400 Feedwater Control System (FWCS). When the performance of the PI controller offers superior control and enhanced robustness, the steam generator (SG) level is properly controlled. This leads to the safe operation and increased the availability of the nuclear power plant. In this paper, a systems engineering approach is used in order to design a novel PI controller for the FWCS. In the reverse engineering stage, the existing FWCS configuration, especially the characteristics of the feedwater controller as well as the feedwater flow path to each SG from the FWCS, were reviewed and analysed. The overall block diagram of the FWCS and the SG was also developed in the reverse engineering process. In the re-engineering stage, the actual design of the feedwater PI controller was carried out using a genetic algorithm (GA). Lastly, in the validation and verification phase, the existing PI controller and the PI controller designed using GA method were simulated in Simulink/Matlab. From the simulation results, the GA-PI controller was found to exhibit greater stability than the current controller of the FWCS.

Keywords

APR 1400 Feedwater Control System; PI Controller; Genetic Algorithm; A Systematic Engineering Approach;

Citations & Related Records

Reference

1	KHNP Nuclear Power Education Institute, APR 1400 Control Systems.
2	J. J. Sohn and P. H. Seong, "A steam generator model identification and robust $H{\infty}$ controller design with v-gap metric for a feedwater control system," Annals of Nuclear Energy, vol. 37, pp. 180-195, 2010. DOI
3	L. Ljung, "Identification for Control: Simple Process Models," Proceedings of the 41st IEEE Conference on Decision and Control, pp. 4652-4657, 2002.
4	B. Naresh, M. Kumar and N. Yadaiah, "GA Based Tuning of PI Controller," IEEE Recent Advances in Intelligent Computational Systems, pp. 321-325, 2011.
5	S. Tsutsui and D. Goldberg, "Search space boundary extension method in real coded genetic algorithm," Information Sciences, vol. 133, pp. 229-247, 2001. DOI
6	A. Mirzal, S. Yoshii and M. Furukawa, "PID Parameters Optimization by Using Genetic Algorithm," ISTECS Journal, vol. 8, pp. 34-43, 2006.
7	L. Fan and E. M. Joo, "Design for Auto-tuning PID Controller Based on Genetic Algorithms," 4th IEEE Conference on Industrial Electronics and Applications, pp. 1924-1928, 2009.
8	The Mathworks Inc., 2018a. [Online]. Available: https://www.mathworks.com. [Accessed 22 10 2018].
9	L. Ljung, System Identification: Theory for the User, second edition, New Jersey: Prentice Hall, 1999.
10	A. Kossiakoff, W. N. Sweet, S. J. Seymour and S. M. Biemer, Systems Engineering Principles and Practice, Wiley-Interscience; 2 edition, 2011.
11	"United States Nuclear Regulatory Commission, APR1400 Design Control," [Online]. Available: https://www.nrc.gov/. [Accessed 5 11 2018].
12	S. J. Ha, C. E. Park, K. D. Kim and C. H. Ban, "Development of The Space Code for Nuclear Power Plants," Nuclear Engineering and Technology, vol. 43, no. 1, pp. 45-62, 2011. DOI