Neural network based regulator for linear and nonlinear dynamic systems
سال انتشار: 1400
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 386
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شناسه ملی سند علمی:
ITCT13_096
تاریخ نمایه سازی: 10 آذر 1400
چکیده مقاله:
The aim of this paper is presenting a new structure based on a neural network for online regulating unknown systems which can be linear and nonlinear. Regulator design in this paper means that building a structure in order to have steady state zero response for any inputs. The proposed structure contains a modelling block based on neural network for unknown system and this block is trained with backpropagation algorithm. In addition, a predictive block is embedded before the unknown plant and a low-pass filter is also applied to reduce the high frequency components of the response at the beginning of the process.
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نویسندگان
Amirreza Ebrahimzadeh sadat
Electrical Engineering Department, Imam Khomeini International University, Qazvin, Iran
Mehdi Rahmani
Electrical Engineering Department, Imam Khomeini International University, Qazvin, Iran