Tuning fuzzy logic controllers using response envelope method

被引:4
作者
Gürocak, HB [1 ]
机构
[1] Washington State Univ, Mfg Engn Program, Vancouver, WA 98686 USA
关键词
fuzzy logic control; engineering; tuning; optimization;
D O I
10.1016/S0165-0114(98)00246-2
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
A fuzzy logic controller (FLC) is designed based on a human expert's knowledge of the process. The performance of this initial design attempt will, in general, not be satisfactory in terms of certain design criteria such as steady-state error, the oscillatory behavior of the system, etc. This is due to the fact that no standard method exists for transforming human knowledge or experience into the rule base of the FLC. In this paper, a method to tune the rule base of an initial FLC design attempt is presented. Results of four experiments are reported and discussed. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:287 / 304
页数:18
相关论文
共 19 条
[1]   LEARNING AND TUNING FUZZY-LOGIC CONTROLLERS THROUGH REINFORCEMENTS [J].
BERENJI, HR ;
KHEDKAR, P .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1992, 3 (05) :724-740
[2]   A PD-like self-tuning fuzzy controller without steady-state error [J].
Chao, CT ;
Teng, CC .
FUZZY SETS AND SYSTEMS, 1997, 87 (02) :141-154
[3]  
Dixon L.C.W, 1972, Nonlinear optimization
[4]  
FOULDS LR, 1981, OPTIMIZATION TECHNIQ
[5]  
Gill M., 1981, Practical Optimization
[6]   A FINE-TUNING METHOD FOR FUZZY-LOGIC RULE BASES [J].
GUROCAK, HB ;
LAZARO, AD .
FUZZY SETS AND SYSTEMS, 1994, 67 (02) :147-161
[7]  
GUROCAK HB, IN PRESS FUZZY SETS
[8]   TUNING FUZZY-LOGIC CONTROLLERS BY GENETIC ALGORITHMS [J].
HERRERA, F ;
LOZANO, M ;
VERDEGAY, JL .
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 1995, 12 (3-4) :299-315
[9]   PLANT-IDENTIFICATION WITH FUZZY INFERENCE AND ITS APPLICATION TO AUTOTUNING [J].
IWASAKI, T ;
MORITA, A ;
MARUYAMA, H .
JSME INTERNATIONAL JOURNAL SERIES C-DYNAMICS CONTROL ROBOTICS DESIGN AND MANUFACTURING, 1995, 38 (03) :457-462
[10]  
KARR CJ, 1993, IEEE T FUZZY SYST, P1