文章基本信息

标题：Adaptive Neuro Fuzzy Inference System PID Controller for AVR System Using SNR-PSO Optimization
本地全文：下载
作者：Kamal Yavarian ; Amir Mohammadian ; Farid Hashemi 等
期刊名称：International Journal on Electrical Engineering and Informatics
印刷版ISSN：2085-6830
出版年度：2015
卷号：7
期号：3
DOI：10.15676/ijeei.2015.7.3.3
出版社：School of Electrical Engineering and Informatics
摘要：This paper presents an intelligent Proportional Integral Derivative (PID)controller for Automatic Voltage Regulator (AVR) system using Adaptive Neuro FuzzyInference System (ANFIS). In the proposed method, the PID controller parameters aretuned off line by using combination of Signal to Noise Ratio (SNR) and Particle SwarmOptimization (PSO) algorithm to minimize the cost function over a wide range ofoperating condition. The optimal values of PID controller parameters obtained fromSNR-PSO algorithm for each considered operating condition are used to train ANFIS.Therefore, the proposed techniques could online tune the PID controller parameters atany other operating condition to improve the transient response of the system. In orderto evaluate the performance of the SNR-PSO PID controller, the results are comparedwith the Genetic Algorithm (GA). Also, the performance of proposed intelligent PIDcontroller is compared with the robust SNR-PSO PID controller with fixed parameters.The comparison shows the SNR-PSO based ANFIS controller is more efficiency thanrobust PID controller.
关键词：Controller; Automatic voltage regulator; Signal to noise ratio; Particle;swarm optimization; Adaptive neuro fuzzy inference system