Title : ( Online tuning of genetic based PID controller in LFC systems using RBF neural network and VSTLF technique )
Authors: Mohammad Monfared , Abbas Molavi Daryani , Mehrdad Abedi ,
Full TextAbstract
In this paper a novel control strategy for load frequency control (LFC) system is proposed. The developed method includes genetic algorithm (GA) based self-tuned PID controller for online application. In this paper a new method is presented in order to regulate PID controller coefficients by radial basis function neural network (RBFN). Furthermore, very short time load forecasting (VSTLF) scheme is also employed as a novel approach for system load variations to be considered in LFC system. For validation of the proposed method several comparative case studies are presented. The simulation results indicate that the proposed strategy improves the system dynamics remarkably.
Keywords
, Load frequency control (LFC), real coded genetic algorithm (RCGA), radial basis function neural network (RBFN), very short time load forecasting (VSTLF)
@article{paperid:1019692,
author = {Monfared, Mohammad and Abbas Molavi Daryani and Mehrdad Abedi},
title = {Online tuning of genetic based PID controller in LFC systems using RBF neural network and VSTLF technique},
journal = {Neural Network World},
year = {2008},
volume = {18},
number = {4},
month = {September},
issn = {1210-0552},
pages = {309--322},
numpages = {13},
keywords = {Load frequency control (LFC); real coded genetic algorithm (RCGA); radial basis function neural network (RBFN); very short time load forecasting (VSTLF)},
}
%0 Journal Article
%T Online tuning of genetic based PID controller in LFC systems using RBF neural network and VSTLF technique
%A Monfared, Mohammad
%A Abbas Molavi Daryani
%A Mehrdad Abedi
%J Neural Network World
%@ 1210-0552
%D 2008
