An Approach to Solving for Multi-Objective Optimization Problem with Application to Linear Motor Control Design

被引:1
|
作者
Lin, C-L.
Jan, H-Y.
机构
[1] Department of Electrical Engineering, National Chung Hsing University, Taichung 402, Taiwan
[2] Institute of Electrical and Information Engineering, Feng Chia University, Taichung 40724, Taiwan
关键词
Evolution algorithm; multi-objective optimization; robust control; linear motor;
D O I
10.2316/Journal.201.2005.2.201-1502
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 authors propose a new design and realization method solving for constrained multi-objective problem via an advanced evolution strategy. Requirements directly related to the H and H2 performance specifications are imposed, which reflect stability robustness and optimality. A modified PID control scheme represented only by two parameters is proposed to control a linear brushless DC motor. The design paradigm offers an effective way to implement robust solutions that covers a wide range of plant perturbations and offers excellent performance. Simulation studies and experiments are performed to verify the performance and applicability of the suggested design.
引用
收藏
页码:75 / 86
页数:2
相关论文
共 50 条
  • [41] Multi-objective optimization approach to the PI tuning problem
    Tavakoli, Saeed
    Griffin, Ian
    Fleming, Peter J.
    2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS, 2007, : 3165 - 3171
  • [42] A multi-objective evolutionary approach to the portfolio optimization problem
    Diosan, Laura
    INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE FOR MODELLING, CONTROL & AUTOMATION JOINTLY WITH INTERNATIONAL CONFERENCE ON INTELLIGENT AGENTS, WEB TECHNOLOGIES & INTERNET COMMERCE, VOL 2, PROCEEDINGS, 2006, : 183 - 187
  • [43] A multi-objective optimization approach for the group formation problem
    Miranda, Pericles B. C.
    Mello, Rafael Ferreira
    Nascimento, Andre C. A.
    EXPERT SYSTEMS WITH APPLICATIONS, 2020, 162 (162)
  • [44] Multi-objective optimization approach to the ALSTOM gasifier problem
    Griffin, IA
    Schroder, P
    Chipperfield, AJ
    Fleming, PJ
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING, 2000, 214 (I6) : 453 - 468
  • [45] A fuzzy goal programming approach for solving fuzzy multi-objective stochastic linear programming problem
    Masoud, Mahmoud
    Khalifa, H. A.
    Liu, Shi Qiang
    Elhenawy, Mohammed
    Wu, Peng
    PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND SYSTEMS MANAGEMENT (IESM 2019), 2019, : 854 - 859
  • [46] Solving multi-objective portfolio optimization problem using invasive weed optimization
    Pouya, Amir Rezaei
    Solimanpur, Maghsud
    Rezaee, Mustafa Jahangoshai
    SWARM AND EVOLUTIONARY COMPUTATION, 2016, 28 : 42 - 57
  • [47] Parallelization of a non-linear multi-objective optimization algorithm: Application to a location problem
    Gila Arrondo, Aranzazu
    Redondo, Juana L.
    Fernandez, Jose
    Ortigosa, Pilar M.
    APPLIED MATHEMATICS AND COMPUTATION, 2015, 255 : 114 - 124
  • [48] The use of a fuzzy multi-objective linear programming for solving a multi-objective single-machine scheduling problem
    Tavakkoli-Moghaddam, Reza
    Javadi, Babak
    Jolai, Fariborz
    Ghodratnama, Ali
    APPLIED SOFT COMPUTING, 2010, 10 (03) : 919 - 925
  • [49] Solving the multi-objective mixed model assembly line problem using a fuzzy multi-objective linear program
    Mahdavi, Iraj
    Javadi, Babak.
    Sabet, S. S.
    ICEIS 2007: PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS: ARTIFICIAL INTELLIGENCE AND DECISION SUPPORT SYSTEMS, 2007, : 370 - 373
  • [50] MOCHIO: a novel Multi-Objective Coronavirus Herd Immunity Optimization algorithm for solving brushless direct current wheel motor design optimization problem
    Kumar, C.
    Mary, D. Magdalin
    Gunasekar, T.
    AUTOMATIKA, 2022, 63 (01) : 149 - 170