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《Chinese Journal of Nuclear Science and Engineering》 2008-02
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CFNN based water level control for nuclear steam generator

SU Ying-bin,XIA Hong,SHEN Ji (College of Nuclear Science and Technology,Harbin Engineering University,Harbin of Heilongjiang Prov.150001,China)  
Because normal PID controller can't change its parameters according to the change of control object parameters.In this paper,the compensatory fuzzy neural network(CFNN) was used with a simplified model of nuclear steam generator(NSG) to design a NSG water level controller.Compensatory neurons which were introduced in the CFNN will make the control system improve the quality of fault tolerant and more stable.Meanwhile compensative fuzzy computation is optimized dynamically in the study algorithm of neural network,therefore the network is much more adaptive and the training speed is much faster.The results of simulation show that under this control method the system has smaller maximum overshoot and faster convergence speed than that of under normal PID control method.The CFNN can not only adjust parameters properly on line,but also can optimized relevant fuzzy reasoning in dynamic way,so it suit to be used on ling learning and control.The control method used in this paper is meaningful to the research of NSG water level intelligent control.
【CateGory Index】: TL353.13
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