Linguistic hedges and fuzzy rule base systems

被引:0
|
作者
Liu, BD [1 ]
机构
[1] Natl Cheng Kung Univ, Dept Elect Engn, Tainan 70101, Taiwan
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A novel fuzzy logic controller called linguistic-hedge fuzzy logic controller and its hardware implementation in a mixed-signal approach is presented in this paper. Several major characteristics of this controller are: 1) only three simple-shape membership functions are required for characterizing each variable; 2) nine rules are enough for inference; 3) both architecture and hardware design complexity are small. For the implementation, a current-mode approach is adopted in designing the signal processing portions to simplify the circuit complexity; digital circuits are adopted to implement the programmable units. This design was fabricated with a TSMC 0.35 mum single-polysilicon-quadruple-metal CMOS process. In this chip, the LHFLC processes two input variables and one output variable. Under a supply voltage of 3.3 V. The speed of inference operation goes up to 0.5M FLIPS that is fast enough for the control application of the cart-pole balance system.
引用
收藏
页码:1724 / 1727
页数:4
相关论文
共 50 条
  • [41] Opinion Mining from Online User Reviews Using Fuzzy Linguistic Hedges
    Dalal, Mita K.
    Zaveri, Mukesh A.
    [J]. APPLIED COMPUTATIONAL INTELLIGENCE AND SOFT COMPUTING, 2014, 2014
  • [42] Expanding the definitions of linguistic hedges
    Shi, HJ
    Ward, R
    Kharma, N
    [J]. JOINT 9TH IFSA WORLD CONGRESS AND 20TH NAFIPS INTERNATIONAL CONFERENCE, PROCEEDINGS, VOLS. 1-5, 2001, : 2591 - 2595
  • [43] A Multiobjective Evolutionary Approach to Concurrently Learn Rule and Data Bases of Linguistic Fuzzy-Rule-Based Systems
    Alcala, Rafael
    Ducange, Pietro
    Herrera, Francisco
    Lazzerini, Beatrice
    Marcelloni, Francesco
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2009, 17 (05) : 1106 - 1122
  • [44] A proposal for the genetic lateral tuning of linguistic fuzzy systems and its interaction with rule selection
    Alcala, Rafael
    Alcala-Fdez, Jesus
    Herrera, Francisco
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2007, 15 (04) : 616 - 635
  • [45] On the use of MapReduce to build Linguistic Fuzzy Rule Based Classification Systems for Big Data
    Lopez, Victoria
    del Rio, Sara
    Manuel Benitez, Jose
    Herrera, Francisco
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2014, : 1905 - 1912
  • [46] Fuzzy inversion and rule base reduction
    Baranyi, P
    Korondi, P
    Hashimoto, H
    Wada, M
    [J]. INES'97 : 1997 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS, PROCEEDINGS, 1997, : 301 - 306
  • [47] Optimal design of a fuzzy rule base
    Ledeneva, T. M.
    Sergienko, M. A.
    [J]. AUTOMATION AND REMOTE CONTROL, 2012, 73 (11) : 1944 - 1949
  • [48] Optimal design of a fuzzy rule base
    T. M. Ledeneva
    M. A. Sergienko
    [J]. Automation and Remote Control, 2012, 73 : 1944 - 1949
  • [49] A rule base modification scheme in fuzzy controllers for time-delay systems
    Genc, Hakki Murat
    Yesil, Engin
    Eksin, Ibrahim
    Guzelkaya, Mujde
    Tekin, Ozgur Aydin
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (04) : 8476 - 8486
  • [50] A non-neural fuzzy rule base approach for modeling complex systems
    Applebaum, E
    [J]. 1997 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS, 1997, : 130 - 135