Multi-objective evolutionary technique based intelligent controllers: Application to control of multivariable nonlinear systems

被引：0
|
作者：
Rahmati, A [1 ]
Rashidi, F [1 ]
机构：
[1] Iran Univ Sci & Technol, Dept Elect Engn, Tehran, Iran
来源：
2004 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN & CYBERNETICS, VOLS 1-7 | 2004年
关键词：
multiobjective evolutionary algorithms; multivariable nonlinear systems; overshoot; rise time; settling time setpoint tracking;
D O I：
10.1109/ICSMC.2004.1400919
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The main objective of this paper is to present a new method based on Multiobjective evolutionary algorithm for control of the multivariable and nonlinear systems. Problem design considers time domain specifications such as overshoot, rising time, settling time and stationary error as well as interaction effects. Genetic algorithms are employed to satisfy time domain design specifications that are not considered in an explicit way in the standard nonlinear control theory. Adaptation, setpoint tracking and satisfaction of temporary response specifications are the advantages of this method that be shown by some simulations.
引用
收藏
页码：3704 / 3708
页数：5
相关论文
共 50 条
  • [1] Design of multi-objective evolutionary technique based intelligent controller for multivariable nonlinear systems
    Rashidi, F
    Rashidi, M
    ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING - ICAISC 2004, 2004, 3070 : 978 - 983
  • [2] Intelligent high-type control based on evolutionary multi-objective optimization
    Zhang, Hanwen
    Liu, Qiong
    Mao, Yao
    MEASUREMENT & CONTROL, 2024, 57 (01): : 51 - 67
  • [3] A multi-objective control approach for nonlinear systems
    Gao, Chen
    Liu, Hugh H. T.
    Zhang, Ping
    ICIA: 2009 INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION, VOLS 1-3, 2009, : 1326 - +
  • [4] Application of an input-output pairings selection methodology to control multivariable systems based on multi-objective optimization
    Huilcapi, Victor
    Blasco, Xavier
    Herrero, Juan M.
    Pajares, Alberto
    Reynoso-Meza, Gilberto
    2021 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI 2021), 2021, : 443 - 449
  • [5] Application of multi-objective evolutionary algorithm in coordinated design of PSS and SVC controllers
    Zou, ZY
    Jiang, QY
    Zhang, PX
    Cao, YJ
    COMPUTATIONAL INTELLIGENCE AND SECURITY, PT 1, PROCEEDINGS, 2005, 3801 : 1106 - 1111
  • [6] Multi-objective evolutionary design of robust controllers on the grid
    Shenfield, Alex
    Fleming, Peter J.
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2014, 27 : 17 - 27
  • [7] Multi-Objective Tuning of Nonlinear PID Controllers for Greenhouse Environment using Evolutionary Algorithms
    Hu, Haigen
    Xu, Lihong
    Wei, Ruihua
    Zhu, Bingkun
    2010 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2010,
  • [8] Multi-objective Nonlinear Control of Semiactive and Regenerative Systems
    Scruggs, J. T.
    2010 AMERICAN CONTROL CONFERENCE, 2010, : 726 - 731
  • [9] Process Control Model PID Controllers Tuned by Multi-objective Evolutionary Adaptive Algorithms
    McLauchlan, Lifford L. L.
    Mehrubeoglu, Mehrube
    IMCIC'11: THE 2ND INTERNATIONAL MULTI-CONFERENCE ON COMPLEXITY, INFORMATICS AND CYBERNETICS, VOL II, 2011, : 62 - 67
  • [10] Epistasis in multi-objective evolutionary recurrent neuro-controllers
    Ventresca, Mario
    Ombuki-Berman, Beatrice
    2007 IEEE SYMPOSIUM ON ARTIFICIAL LIFE, 2006, : 77 - +
12345