Design and optimization of fuzzy-PID controller for the nuclear reactor power control

被引:116
作者
Liu, Cheng [1 ]
Peng, Jin-Feng [1 ]
Zhao, Fu-Yu [1 ]
Li, Chong [1 ]
机构
[1] Xi An Jiao Tong Univ, Sch Energy & Power Engn, Xian 710049, Shaanxi, Peoples R China
关键词
Compendex;
D O I
10.1016/j.nucengdes.2009.07.001
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
This paper introduces a fuzzy proportional-integral-derivative (fuzzy-PID) control strategy, and applies it to the nuclear reactor power control system. At the fuzzy-PI D control strategy, the fuzzy logic controller (FLC) is exploited to extend the finite sets of PID gains to the possible combinations of PID gains in stable region and the genetic algorithm to improve the 'extending' precision through quadratic optimization for the membership function (MF) of the FLC. Thus the FLC tunes the gains of PID controller to adapt the model changing with the power. The fuzzy-PID has been designed and simulated to control the reactor power. The simulation results show the favorable performance of the fuzzy-PID controller. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:2311 / 2316
页数:6
相关论文
共 14 条
[1]  
CHEN C, 2008, GRANULAR COMPUTING, P115, DOI DOI 10.1109/GRC.2008.4664771
[2]  
CIPRIAN L, 2008, UPB SCI B C, V70, P97
[3]   Risk-based, genetic algorithm approach to optimize outage maintenance schedule [J].
Hadavi, S. Mohammad Hadi .
ANNALS OF NUCLEAR ENERGY, 2008, 35 (04) :601-609
[4]  
ISMAEL MM, 2006, P WORLD C INT CONTR, V1, P134
[5]  
JOSE A, 2008, ANN NUCL ENERGY, V35, P576
[6]   THEORETICAL AND EXPERIMENTAL DYNAMIC ANALYSIS OF ROBINSON,HB NUCLEAR-PLANT [J].
KERLIN, TW ;
KATZ, EM ;
THAKKAR, JG ;
STRANGE, JE .
NUCLEAR TECHNOLOGY, 1976, 30 (03) :299-316
[7]   Robust controller design for multivariable nonlinear systems via multi-model H2/H∞ synthesis [J].
Kolavennu, S ;
Palanki, S ;
Cockburn, JC .
CHEMICAL ENGINEERING SCIENCE, 2001, 56 (14) :4339-4349
[8]  
LUO W, 2008, P SPIE INT SOC OPTIC, V7129
[9]   Genetic algorithm optimization of a model-free fuzzy control system [J].
Marseguerra, M ;
Zio, E ;
Cadini, F .
ANNALS OF NUCLEAR ENERGY, 2005, 32 (07) :712-728
[10]  
Narvydas G, 2007, INT WORKSH INT DATA, P460