Tuning PID Controller Using Hybrid Genetic Algorithm Particle Swarm Optimization Method for AVR System

被引：0

作者：

Aboura, Faouzi ^{[1
]}

机构：

[1] Univ Sci & Technol Houari Boumed, Lab Syst Elect & Ind LSEI, Bab Ezzouar 16123, Algeria

来源：

2019 INTERNATIONAL AEGEAN CONFERENCE ON ELECTRICAL MACHINES AND POWER ELECTRONICS (ACEMP) & 2019 INTERNATIONAL CONFERENCE ON OPTIMIZATION OF ELECTRICAL AND ELECTRONIC EQUIPMENT (OPTIM) | 2019年

关键词：

PID controller; AVR system; objective function; optimization; GA; PSO; HGAPSO; AUTOMATIC VOLTAGE REGULATOR; DESIGN;

D O I：

10.1109/acemp-optim44294.2019.9007124

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The proportional-integral-derivative (PID) controller is widely used in industrial applications, one of these important application is the Automatic Voltage Regulator (AVR), due to the necessity of using controller to avoid instability of the system. In our paper a comparison between algorithms Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) and Hybrid Genetic Algorithm Particle Swarm Optimization (HGAPSO) is proposed with their characteristics and performance analysis to find an optimum parameters of the PID controller, a new objective function is also proposed to take into account the relation between the performance criteria's

引用

页码：570 / 574

页数：5

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