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
  • [41] CONTROLLING INTERACTIONS BY A PI-MULTIVARIABLE CONTROLLER
    PELTOMAA, A
    KOIVO, H
    PAPERI JA PUU-PAPER AND TIMBER, 1982, 64 (04): : 239 - 242
  • [42] On stabilizing PI controller ranges for multivariable systems
    Lin, Chong
    Wang, Qing-Guo
    He, Yong
    He, Yong
    Wen, Guilin
    Han, Xu
    Li, Guangyao
    Zhong, Zhi-Hua
    CHAOS SOLITONS & FRACTALS, 2008, 35 (03) : 620 - 625
  • [43] Multiobjective evolutionary algorithms on complex networks
    Kirley, Michael
    Stewart, Robert
    EVOLUTIONARY MULTI-CRITERION OPTIMIZATION, PROCEEDINGS, 2007, 4403 : 81 - +
  • [44] Benchmarking evolutionary multiobjective optimization algorithms
    Mersmann, Olaf
    Trautmann, Heike
    Naujoks, Boris
    Weihs, Claus
    2010 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2010,
  • [45] On Utilizing Infeasibility in Multiobjective Evolutionary Algorithms
    Hanne, Thomas
    MULTIOBJECTIVE PROGRAMMING AND GOAL PROGRAMMING: THEORETICAL RESULTS AND PRACTICAL APPLICATIONS, 2009, 618 : 113 - 122
  • [46] Design of robot controller based on evolutionary algorithms and neural networks
    Avdagic, Z
    Konjicija, S
    6TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL XII, PROCEEDINGS: INDUSTRIAL SYSTEMS AND ENGINEERING II, 2002, : 548 - 553
  • [47] Evolutionary Algorithms to Analyse and Design a Controller for a Flapping Wings Aircraft
    Doncieux, Stephane
    Hamdaoui, Mohamed
    NEW HORIZONS IN EVOLUTIONARY ROBOTICS: EXTENDED CONTRIBUTIONS FROM THE 2009 EVODEROB WORKSHOP, 2011, 341 : 67 - +
  • [48] Feedback controller design for a boost converter through evolutionary algorithms
    Sundareswaran, Kinattingal
    Devi, Vadakke
    Sankar, Selvakumar
    Srininivasa, Panugothu
    Nayak, Rao
    Peddapati, Sankar
    IET POWER ELECTRONICS, 2014, 7 (04) : 903 - 913
  • [49] Feedback controller design for a buck converter through evolutionary algorithms
    Sundareswaran, K
    Devi, V.
    Sankar, S
    Nayak, P.S.R.
    Chandrasekhar, A.
    Australian Journal of Electrical and Electronics Engineering, 2013, 10 (04): : 467 - 482
  • [50] Multivariable Controller Design with Integrity
    Kallakuri, P.
    Keel, L. H.
    Bhattacharyya, S. P.
    2013 AMERICAN CONTROL CONFERENCE (ACC), 2013, : 5159 - 5164
12345