Browse > Article
http://dx.doi.org/10.1016/j.net.2020.07.037

Design of the flexible switching controller for small PWR core power control with the multi-model  

Zeng, Wenjie (School of Nuclear Science and Technology, University of South China)
Jiang, Qingfeng (School of Nuclear Science and Technology, University of South China)
Du, Shangmian (School of Nuclear Science and Technology, University of South China)
Hui, Tianyu (School of Nuclear Science and Technology, University of South China)
Liu, Yinuo (School of Nuclear Science and Technology, University of South China)
Li, Sha (Shenzhen Xinbang Protection Technology Co., Ltd)
Publication Information
Nuclear Engineering and Technology / v.53, no.3, 2021 , pp. 851-859 More about this Journal
Abstract
Small PWR can be used for power generation and heating. Considering that small PWR has the characteristics of flexible operating conditions and complex operating environment, the controller designed based on single power level is difficult to achieve the ideal control of small PWR in the whole range of core power range. To solve this problem, a flexible switching controller based on fuzzy controller and LQG/LTR controller is designed. Firstly, a core fuzzy multi-model suitable for full power range is established. Then, T-S fuzzy rules are designed to realize the flexible switching between fuzzy controller and LQG/LTR controller. Finally, based on the core power feedback principle, the core flexible switching control system of small PWR is established and simulated. The results show that the flexible switching controller can effectively control the core power of small PWR and the control effect has the advantages of both fuzzy controller and LQG/LTR controller.
Keywords
Small PWR; Fuzzy multi-model; Flexible switching controller; Core power;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Yan-cheng Zhang, Research on Fuzzy Control and Simulation of Vehicle Active Suspension Based on Matlab/Simulink, Liaoning University of Technology, Liaoning, 2014.
2 Yu Hai-liang, The Application of LQG/LTR Method in Turntable System, Harbin Institute of Technology, Harbin, 2013.
3 Wen-Jie Zeng, et al., LQG/LTR controller with simulated annealing algorithm for CIADS core power control, Ann. Nucl. Energy 142 (2020), https://doi.org/10.1016/j.anucene.2020.107422, 2020.   DOI
4 Qiang Zhang, Multi-mode Soft Switching Variable Pitch Control of Wind Turbines Based on T-S Fuzzy Weighted, Lanzhou Jiaotong University, Lanzhou, 2019.
5 Ping Hu, Fu-Yu Zhao, Tai Yun, Coordination control and simulation for small nuclear power plant, Prog. Nucl. Energy 58 (2012) 21-26, https://doi.org/10.1016/j.pnucene.2012.02.001.   DOI
6 L. Wang, X. Wei, F. Zhao, X. Fu, Modification and analysis of load follow control without boron adjustment for CPR1000, Ann. Nucl. Energy 70 (2014) (2014) 317-328, https://doi.org/10.1016/j.anucene.2013.12.001.   DOI
7 Tai Yun, Hou Su-xia, Li Chong, Fu-Yu Zhao, An improved implicit multiple model predictive control used for movable nuclear power plant, Nucl. Eng. Des. 240 (2010) 3582-3585, https://doi.org/10.1016/j.nucengdes.2010.05.003.   DOI
8 Wenjie Zeng, Qingfeng Jiang, Jinsen Xie, Yu Tao, A functional variable universe fuzzy PID controller for load following operation of PWR with the multiple model, Ann. Nucl. Energy 140 (2020), https://doi.org/10.1016/j.anucene.2019.107174.   DOI
9 Lezhi Chen, Wenjie Zeng, Tao Yu, Jinsen Xie, Shangmian Du, Run Luo, Development and application of fuzzy multiple model simulation system for nuclear reactor core, Nucl. Power Eng. 40 (2019) 146-149.
10 Wenjie Zeng, Qingfeng Jiang, Jinsen Xie, Yu Tao, A fuzzy-PID composite controller for core power control of liquid molten salt reactor[J], Ann. Nucl. Energy 139 (2020), https://doi.org/10.1016/j.anucene.2019.107234.   DOI
11 Liao Long-tao, Peng-Fei Wang, Study of multi-model internal model robust control for a small pressurized water reactor core, Autom. Instrum. 33 (2018) 76-79. + 94.
12 F. Dumortier, A. Van Cauwenberghe, L. Boullart, Computer Aided Design of Advanced Control Algorithms for Nuclear Reactor Control, 1994, https://doi.org/10.1109/CACSD, 04/1994.
13 G. Li, X. Wang, B. Liang, X. Li, B. Zhang, Y. Zou, Modeling and control of nuclear reactor cores for electricity generation: a review of advanced technologies, Renew. Sustain. Energy Rev. 60 (2016) 116-128, https://doi.org/10.1016/j.rser.2016.01.116.   DOI
14 Chao-Jie Xie, Study of Membership Function Self-Adjusting Fuzzy Controller, Xi'an University of Electronic Science and Technology of China, Xi'an, 2014.
15 Gang Li, Fu-Yu Zhao, Flexibility control and simulation with multi-model and LQG/LTR design for PWR core load following operation, Ann. Nucl. Energy 68 (2013) 193-203, https://doi.org/10.1016/j.anucene.2013.01.035.   DOI
16 Andres Etchepareborda, Jose Lolich, Research reactor power control design using an output feedback nonlinear design, Nucl. Eng. Des. 277 (2007) 268-276, https://doi.org/10.1016/j.nucengdes.2006.04.002.   DOI