Multiobjective evolutionary algorithms for multivariable PI controller design

被引：37
|
作者：
Reynoso-Meza, Gilberto [1 ]
Sanchis, Javier [1 ]
Blasco, Xavier [1 ]
Herrero, Juan M. [1 ]
机构：
[1] Univ Politecn Valencia, Inst Univ Automat & Informat Ind, Grp Control Predictivo & Optimizac Heurist CPOH, Valencia 46022, Spain
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2012年 / 39卷 / 09期
关键词：
Multiobjective optimisation; Controller tuning; PID tuning; Multiobjective evolutionary optimisation; Decision making; DIFFERENTIAL EVOLUTION; PARETO FRONT; OPTIMIZATION; ROBUST;
D O I：
10.1016/j.eswa.2012.01.111
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A multiobjective optimisation engineering design (MOED) methodology for PI controller tuning in multivariable processes is presented. The MOED procedure is a natural approach for facing multiobjective problems where several requirements and specifications need to be fulfilled. An algorithm based on the differential evolution technique and spherical pruning is used for this purpose. To evaluate the methodology, a multivariable control benchmark is used. The obtained results validate the MOED procedure as a practical and useful technique for parametric controller tuning in multivariable processes. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码：7895 / 7907
页数：13
相关论文
共 50 条
  • [31] Multiobjective gas turbine engine controller design using genetic algorithms
    Chipperfield, A
    Fleming, P
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 1996, 43 (05) : 583 - 587
  • [32] Multivariable controller tuning by genetic algorithms
    Atanasijevic-Kunc, M
    Karba, R
    ITI 2000: PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY INTERFACES, 2000, : 337 - 342
  • [33] Use of multiobjective evolutionary algorithms in high brightness electron source design
    Bazarov, IV
    Senderovich, I
    Sinclair, CK
    2005 IEEE PARTICLE ACCELERATOR CONFERENCE (PAC), VOLS 1-4, 2005, : 4078 - 4080
  • [34] Design of Constellations for GNSS Reflectometry Mission Using the Multiobjective Evolutionary Algorithms
    Xu, Xiaohua
    Ju, Zhanghai
    Luo, Jia
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [35] Novel Fibre Bragg Grating design using multiobjective evolutionary algorithms
    Manos, S
    Poladian, L
    CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS, 2003, : 2089 - 2095
  • [36] Design of Constellations for GNSS Reflectometry Mission Using the Multiobjective Evolutionary Algorithms
    Xu, Xiaohua
    Ju, Zhanghai
    Luo, Jia
    IEEE Transactions on Geoscience and Remote Sensing, 2022, 60
  • [37] Evolutionary algorithms based multiobjective optimization techniques for intelligent systems design
    Jee, MA
    Esbensen, H
    1996 BIENNIAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS, 1996, : 360 - 364
  • [38] Multiobjective design optimization of electrostatic rotary microactuators using evolutionary algorithms
    Di Barba, Paolo
    Wiak, Slawomir
    ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING - ICAISC 2006, PROCEEDINGS, 2006, 4029 : 344 - 353
  • [39] On Benchmarking Interactive Evolutionary Multiobjective Algorithms
    Shavarani, Seyed Mahdi
    Lopez-Ibanez, Manuel
    Knowles, Joshua
    IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2024, 28 (04) : 1084 - 1098
  • [40] An Overview of Evolutionary Algorithms in Multiobjective Optimization
    Fonseca, Carlos M.
    Fleming, Peter J.
    EVOLUTIONARY COMPUTATION, 1995, 3 (01) : 1 - 16
12345