Reduction of the number of rules in fuzzy controllers using genetic algorithm

被引：0
|
作者：
Belarbi, K [1 ]
Filali, S [1 ]
Talbi, N [1 ]
Boutamina, B [1 ]
机构：
[1] Univ Constantine, Lab Automat & Robot, Constantine, Algeria
来源：
2004 IEEE International Conference on Industrial Technology (ICIT), Vols. 1- 3 | 2004年
关键词：
fuzzy logic; fuzzy controllers; genetic algorithm; optimisation;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A procedure for designing a Mamdani fuzzy logic controller including rule base reduction is proposed. The rules are modelled with binary weights on which constraints are imposed in order to ensure consistency. A simple genetic algorithm is used for finding stabilising controllers that minimise the number of rules. The design procedure involves the rule base and the distribution of the fuzzy sets in the universes of discourses. As an example the control of the pole and cart system is studied. The optimisation procedure produced compact fuzzy controllers with five rules having relatively good robustness properties.
引用
收藏
页码：1112 / 1115
页数：4
相关论文
共 50 条
  • [31] Application of genetic algorithm in optimization of fuzzy control rules
    Zhang, JingYuan
    Li, YeDe
    ISDA 2006: SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, VOL 1, 2006, : 529 - 532
  • [32] Service composition based on genetic algorithm and fuzzy rules
    Gheisari, Mohammad Reza
    Emadi, Sima
    INTERNATIONAL JOURNAL OF KNOWLEDGE-BASED AND INTELLIGENT ENGINEERING SYSTEMS, 2022, 26 (03) : 201 - 217
  • [33] Fuzzy membership functions optimization of fuzzy controllers for a quad rotor using particle swarm optimization and genetic algorithm
    Safaee, Bita
    Mashhadi, Seyed Kamaleddin Mousavi
    2016 4TH INTERNATIONAL CONFERENCE ON CONTROL, INSTRUMENTATION, AND AUTOMATION (ICCIA), 2016, : 256 - 261
  • [34] Fuzzy controllers with conditionally firing rules
    Moser, B
    Navara, M
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2002, 10 (03) : 340 - 348
  • [35] Environmental/economic dispatch using genetic algorithm and fuzzy number ranking method
    Zhang, Guangquan
    Zhang, Guoli
    Lu, Jie
    Lu, Haiyan
    APPLIED ARTIFICIAL INTELLIGENCE, 2006, : 59 - +
  • [36] Optimal and stable fuzzy controllers for nonlinear systems subject to parameter uncertainties using genetic algorithm
    Lam, HK
    Ling, SH
    Leung, FHF
    Tam, PKS
    10TH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-3: MEETING THE GRAND CHALLENGE: MACHINES THAT SERVE PEOPLE, 2001, : 908 - 911
  • [37] Optimization of fuzzy inference rules by using the genetic algorithm and its application to the bond rating
    Tan, KR
    Tokinaga, S
    JOURNAL OF THE OPERATIONS RESEARCH SOCIETY OF JAPAN, 1999, 42 (03) : 302 - 315
  • [38] Enhancing Customer Relationship Management Using Fuzzy Association Rules and the Evolutionary Genetic Algorithm
    Dahab, Ahmed Abu-Al
    Haggag, Riham M.
    Fotouh, Samir Abu-Al
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2023, 14 (04) : 639 - 649
  • [39] Extraction and optimization of fuzzy association rules using multi-objective genetic algorithm
    Thilagam, P. Santhi
    Ananthanarayana, V. S.
    PATTERN ANALYSIS AND APPLICATIONS, 2008, 11 (02) : 159 - 168
  • [40] Generating fuzzy rules for target tracking using a steady-state genetic algorithm
    Chan, Keith C.C.
    Lee, Vika
    Leung, Henry
    IEEE Transactions on Evolutionary Computation, 1997, 1 (03): : 189 - 200
12345