Optimization of Fractional and Integer Order PID Parameters using Big Bang Big Crunch and Genetic Algorithms for a MAGLEV System

被引：20
|
作者：
Altintas, Gokhan [1 ]
Aydin, Yucel [2 ]
机构：
[1] Istanbul Tech Univ, Elect Engn Dept, Istanbul, Turkey
[2] Istanbul Tech Univ, Control & Automat Engn Dept, Istanbul, Turkey
来源：
IFAC PAPERSONLINE | 2017年 / 50卷 / 01期
关键词：
Evolutionary algorithms; Modeling for control optimization; Fractional systems; Optimal control theory; Static optimization problems; Design methodologies;
D O I：
10.1016/j.ifacol.2017.08.978
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a study on optimized control for a magnetically levitated (MAGLEV) suspension system. Unstable magnetically levitated system is modelled and integer order PID (IOPID) and fractional order PID (FOPID) controller parameters are evaluated by using both Genetic Algorithm (GA) and Big Bang Big Crunch (BBBC) algorithm. Comparison between BBBC and GA based controllers are done. Responses for variable reference inputs are obtained. Results show that the performance of the BBBC based FOPID controller is better than GA optimized FOPID controller. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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页码：4881 / 4886
页数：6
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