An accurate and cost-effective COG defuzzifier without the multiplier and the divider

被引:6
作者
Kim, D [1 ]
Cho, IH [1 ]
机构
[1] DongA Univ, Dept Comp Engn, Pusan 604714, South Korea
关键词
fuzzy logic controller; COG defuzzifier; moment equilibrium point; stochastic computing; coarse-to-fine searching; truck backer-upper control;
D O I
10.1016/S0165-0114(97)00199-1
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper proposes an accurate and cost-effective COG defuzzifier of fuzzy logic controller (FLC). The accuracy of the proposed COG defuzzifier is obtained by involving both membership values and spans of membership functions in calculating a crisp value. The cost-effectiveness of the proposed COG defuzzifier is obtained by finding the moment equilibrium point instead of computing the division in the COG defuzzifier. The proposed COG defuzzifier has two disadvantages: it increases the hardware complexity due to the additional multipliers and it takes a lot of computation time to find the moment equilibrium point. The first disadvantage is overcome by replacing the multipliers with the stochastic AND operations. The second disadvantage is alleviated by using a coarse-to-fine searching algorithm that accelerates the finding of moment equilibrium point by O(M) maximally when compared with the equal interval searching method of Ruiz et al. (1995). Application of the proposed COG defuzzifier to the truck backer-upper control problem is performed in the VHDL simulation and the control accuracy of the proposed COG defuzzifier is compared with that of the conventionally simplified COG defuzzifier in terms of average tracing distance. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:229 / 244
页数:16
相关论文
共 11 条
[1]  
[Anonymous], IND APPL FUZZY CONTR
[2]  
Gloster C. S. Jr., 1988, International Test Conference 1988 Proceedings - New Frontiers in Testing (Cat. No.88CH2610-4), P138, DOI 10.1109/TEST.1988.207791
[3]   ARCHITECTURE AND STATISTICAL-MODEL OF A PULSE-MODE DIGITAL MULTILAYER NEURAL-NETWORK [J].
KIM, YC ;
SHANBLATT, MA .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1995, 6 (05) :1109-1118
[4]   FUNCTIONAL ABILITIES OF A STOCHASTIC LOGIC NEURAL NETWORK [J].
KONDO, Y ;
SAWADA, Y .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1992, 3 (03) :434-443
[5]  
LEE CC, 1990, IEEE T SYST MAN CYB, V22, P403
[6]  
RUIZ A, 1995, IEEE MICRO, V15, P1
[7]  
RUNKLER TA, 1993, SECOND IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1 AND 2, P1161, DOI 10.1109/FUZZY.1993.327350
[8]   THE ANALYSIS OF ONE-DIMENSIONAL LINEAR CELLULAR AUTOMATA AND THEIR ALIASING PROPERTIES [J].
SERRA, M ;
SLATER, T ;
MUZIO, JC ;
MILLER, DM .
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 1990, 9 (07) :767-778
[9]  
*SYN CORP, 1994, SNY VSS FAM TUT
[10]   GENERATING FUZZY RULES BY LEARNING FROM EXAMPLES [J].
WANG, LX ;
MENDEL, JM .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1992, 22 (06) :1414-1427