Comparison of classical control and intelligent control for a MIMO system

被引:56
|
作者
Juang, Jih-Gau [1 ]
Lin, Ren-Wei [1 ]
Liu, Wen-Kai [1 ]
机构
[1] Natl Taiwan Ocean Univ, Dept Commun & Guidance Engn, Chilung, Taiwan
关键词
Classical control; Intelligent control; Fuzzy system; Genetic algorithm; MIMO system;
D O I
10.1016/j.amc.2008.05.061
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper presents several classical control schemes and intelligent control schemes of an experimental propeller setup, which is called the twin rotor multi-input multi-output (MIMO) system. The objective of this study is to decouple the twin rotor MIMO system into the horizontal plane and vertical plane, and perform setpoint control that makes the beam of the twin rotor MIMO system move quickly and accurately in order to track a trajectory or to reach specified positions. We utilize the conventional control and intelligent control techniques in the vertical and horizontal planes of the twin rotor MIMO system. In classical control, three of the most popular controller design techniques are utilized in this study. These are the Ziegler-Nichols Proportional-Integral-Derivative (PID) rule, the gain margin and phase margin rule, and the pole placement method. Intelligent control is also proposed in this paper in order to improve the attitude tracking accuracy of the twin rotor MIMO system. Intelligent control designs are based on fuzzy logic system and genetic algorithm. Simulations show that the intelligent controllers have better performance than the classical controllers. (C) 2008 Elsevier Inc. All rights reserved.
引用
下载
收藏
页码:778 / 791
页数:14
相关论文
共 50 条
  • [31] Intelligent Lighting Control System
    Garcia, Elena
    Rodriguez, Sara
    De Paz, Juan F.
    Bajo, Javier
    DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE, 11TH INTERNATIONAL CONFERENCE, 2014, 290 : 195 - 207
  • [32] INTELLIGENT TRAFFIC CONTROL SYSTEM
    Bilal, Jubair Mohammed
    Jacob, Don
    ICSPC: 2007 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATIONS, VOLS 1-3, PROCEEDINGS, 2007, : 496 - 499
  • [33] Performance comparison between classical and quantum control for a simple quantum system
    Xi, Zairong
    Jin, Guangsheng
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2008, 387 (04) : 1056 - 1062
  • [34] Performance comparison between classical and quantum control for a simple quantum system
    Xi Zairong
    Proceedings of the 26th Chinese Control Conference, Vol 6, 2007, : 586 - 588
  • [35] Development of a laboratory module for intelligent and classical control classes
    Duysak, Alpaslan
    Unsal, Abdurrahman
    Schiano, Jeffrey L.
    ENERGY EDUCATION SCIENCE AND TECHNOLOGY PART B-SOCIAL AND EDUCATIONAL STUDIES, 2012, 4 (03): : 1405 - 1416
  • [36] Classical and Intelligent Based Control Method for Positioning Systems
    Yakub, Fitri
    Mori, Yasuchika
    Andika, Aji Wijaya
    2015 34TH CHINESE CONTROL CONFERENCE (CCC), 2015, : 4239 - 4244
  • [37] Intelligent control algorithm for dynamic positioning control system
    Guan, Hongqiang
    FRONTIERS IN MECHANICAL ENGINEERING-SWITZERLAND, 2024, 10
  • [38] Intelligent Reconfigurable Control System for Aircraft Flight Control
    Terrell, Kevin
    Zein-Sabatto, Saleh
    SOUTHEASTCON 2017, 2017,
  • [39] Design and Control of an Intelligent Electronic Throttle Control System
    Yadav, Anil Kumar
    Gaur, Prerna
    Tripathi, Sandeep
    2015 INTERNATIONAL CONFERENCE ON ENERGY ECONOMICS AND ENVIRONMENT (ICEEE), 2015,
  • [40] The UPFC intelligent control system based on human-simulated intelligent control
    Chen, Z
    Yan, W
    Xu, G
    Wang, GJ
    2003 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-5, PROCEEDINGS, 2003, : 736 - 740