A "mutual update" training algorithm for fuzzy adaptive logic control/decision network (FALCON)

被引:5
作者
Altug, S [1 ]
Trussell, HJ [1 ]
Chow, MY [1 ]
机构
[1] N Carolina State Univ, Dept Elect & Comp Engn, Raleigh, NC 27695 USA
来源
IEEE TRANSACTIONS ON NEURAL NETWORKS | 1999年 / 10卷 / 01期
关键词
adaptation; artificial neural networks; fault detection and diagnosis; mutual update; training;
D O I
10.1109/72.737508
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The conventional two-stage training algorithm of the fuzzy/neural architecture called FALCON may not provide accurate results for certain type of problems, due to the implicit assumption of independence that this training makes about parameters of the underlying fuzzy inference system. In this correspondence, a training scheme is proposed for this fuzzy/neural architecture, which is based on line search methods that have long been used in iterative optimization problems. This scheme involves synchronous update of the parameters of the architecture corresponding to input and output space partitions and rules defining the underlying mapping; the magnitude and direction of the update at each iteration is determined using the Armijo rule. In our motor fault detection study case, the mutual update algorithm arrived at the steady-state error of the conventional FALCON training algorithm as twice as fast and produced a low er steady-state error by an order of magnitude.
引用
收藏
页码:196 / 199
页数:4
相关论文
共 7 条
[1]  
[Anonymous], 1997, Methodologies of Using Neural Network and Fuzzy Logic Technologies for Motor Incipient Fault Detection
[2]  
ARMIJO L, 1966, PAC J MATH, P1
[3]   USING A NEURAL FUZZY SYSTEM TO EXTRACT HEURISTIC KNOWLEDGE OF INCIPIENT FAULTS IN INDUCTION-MOTORS .1. METHODOLOGY [J].
GOODE, PV ;
CHOW, M .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 1995, 42 (02) :131-138
[4]  
KELLEY CT, 1995, ITERATIVE METHODS LI
[5]  
Lin C.T., 1996, NEURAL FUZZY SYSTEMS
[6]   NEURAL-NETWORK-BASED FUZZY-LOGIC CONTROL AND DECISION SYSTEM [J].
LIN, CT ;
LEE, CSG .
IEEE TRANSACTIONS ON COMPUTERS, 1991, 40 (12) :1320-1336
[7]  
Luenberger D.G., 1989, LINEAR NONLINEAR PRO