کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8069307 | 1521129 | 2014 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Power level control of the TRIGA Mark-II research reactor using the multifeedback layer neural network and the particle swarm optimization
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
مهندسی انرژی و فناوری های برق
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Power level control of the TRIGA Mark-II research reactor using the multifeedback layer neural network and the particle swarm optimization Power level control of the TRIGA Mark-II research reactor using the multifeedback layer neural network and the particle swarm optimization](/preview/png/8069307.png)
چکیده انگلیسی
In this paper, an artificial neural network controller is presented using the Multifeedback-Layer Neural Network (MFLNN), which is a recently proposed recurrent neural network, for neutronic power level control of a nuclear research reactor. Off-line learning of the MFLNN is accomplished by the Particle Swarm Optimization (PSO) algorithm. The MFLNN-PSO controller design is based on a nonlinear model of the TRIGA Mark-II research reactor. The learning and the test processes are implemented by means of a computer program at different power levels. The simulation results obtained reveal that the MFLNN-PSO controller has a remarkable performance on the neutronic power level control of the reactor for tracking the step reference power trajectories.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Annals of Nuclear Energy - Volume 69, July 2014, Pages 260-266
Journal: Annals of Nuclear Energy - Volume 69, July 2014, Pages 260-266
نویسندگان
Ramazan Coban,