SUCCESSIVE IDENTIFICATION OF A FUZZY MODEL AND ITS APPLICATIONS TO PREDICTION OF A COMPLEX SYSTEM

被引：315
|
作者：
SUGENO, M
TANAKA, K
机构：
[1] Department of Systems Science, Tokyo Institute of Technology, Midori-ku, Yokohama, 227
来源：
FUZZY SETS AND SYSTEMS | 1991年 / 42卷 / 03期
关键词：
FUZZY MODEL; SUCCESSIVE FUZZY MODELING; CONTRAST INTENSIFICATION; FUZZY ADJUSTMENT RULE;
D O I：
10.1016/0165-0114(91)90110-C
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
A successive identification method of a fuzzy model is suggested. The identification mechanism consists of two levels. One is the supervisor level and the other is the adjustment level. The supervisor level determines a policy of parameter adjustment using a set of fuzzy adjustment rules. The adjustment rules are derived from the fuzzy implications of a fuzzy model and are extended to fuzzy adjustment rules by using an extended concept of Zadeh's contrast intensification. The adjustment level executes the policy of parameter adjustment determined with the fuzzy adjustment rules. The parameter adjustment consists of premise parameter adjustment and consequent parameter adjustment. Both of them are realized by the weighted recursive least square algorithm. Finally, it is shown from two examples that the method is very useful for modeling complex systems.
引用
收藏
页码：315 / 334
页数：20
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