A Neural Network Controller for Load Following Operation of Nuclear Reactors
Publish place: 16th International Power System Conference
Publish Year: 1380
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
PSC16_089
تاریخ نمایه سازی: 3 مهر 1386
Abstract:
Nuclear reactors are in nature nonlinear and their parameters vary with time as a function of power level, fuel burnup, and control rod worth. Therefore, these characteristics must be considered if large power variations occur in power plant working regimes (for example in load following conditions). In this paper a Neural Network Controller (NNC) is presented. A Robust Optimal Regulator (ROSTR)[1] response is used as a reference Self-Tuning
trajectory to determine the feedback, feedforward and observer gains of the NNC. The NNC has displayed good stability and performance for a wide range of operation as well as considerable reduction in computation time in regard to ROSTR and Fuzzy Logic Controller (FAROC) [2].
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Authors
MEHRDAD KHAJAVI
Training Manager Iran Energy Efficiency Organization (SABA)
MOHAMMAD MENHAJ
Associate Prof. School of computer and electrical engineering. Oklahoma State University Oklahoma, U.S.A
AMIR SURATGAR
Amir-Kabir University ofTechnology Electrical Engineering Department, Tehran Iran.