Design Methodology for the Implementation of Fuzzy Inference Systems Based on Boolean Relations

被引:19
作者
Espitia, Helbert [1 ]
Soriano, Jose [1 ]
Machon, Ivan [2 ]
Lopez, Hilario [2 ]
机构
[1] Univ Dist Francisco Jose de Caldas, Fac Ingn, Bogota 111321, Colombia
[2] Univ Oviedo, Dept Ingn Elect Elect Computadores & Sistemas, Campus Viesques, Gijon Xixon 33204, Spain
关键词
Boolean relations; control; design methodology; fuzzy logic; SETS;
D O I
10.3390/electronics8111243
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes a methodology for the design of fuzzy inference systems based on Boolean relations. The approach using Boolean sets presents limited performance due to the abrupt transitions that occur during its functioning, therefore, fuzzy sets can be used aiming the improvement of the performance. In this approach, firstly, the design of a Boolean controller is performed, which is later extended into fuzzy under design guidelines proposed in this paper. The methodology uses Kleene algebra via truth tables for the fuzzy system design, allowing the simplification of the equations that implement the fuzzy system.
引用
收藏
页数:28
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共 50 条
  • [1] [Anonymous], 2010, REV ING
  • [2] [Anonymous], 1995, Fuzzy Sets and Fuzzy Logic
  • [3] A new T-S fuzzy model predictive control for nonlinear processes
    Boulkaibet, Ilyes
    Belarbi, Khaled
    Bououden, Sofiane
    Marwala, Tshilidzi
    Chadli, Mohammed
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2017, 88 : 132 - 151
  • [4] Fuzzy model reference control with adaptation mechanism
    Cerman, Otto
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2013, 40 (13) : 5181 - 5187
  • [5] Chamorro H.R., 2011, P IEEE ANN M N AM FU
  • [6] Clark TD, 2008, STUD FUZZ SOFT COMP, V225, P1, DOI 10.1007/978-3-540-77461-7
  • [7] Fuzzy decision method to improve the information exchange in a vehicle sensor tracking system
    Cueva-Fernandez, Guillermo
    Pascual Espada, Jordan
    Garcia-Diaz, Vicente
    Gonzalez-Crespo, Ruben
    [J]. APPLIED SOFT COMPUTING, 2015, 35 : 708 - 716
  • [8] Czogala E, 2000, STUD FUZZ SOFT COMP, V47, P1
  • [9] Doebelin E., 2012, CONTROL SYSTEM PRINC
  • [10] Dougherty EdwardR., 1988, Mathematical methods for artificial intelligence and autonomous systems