Title
Neuro-Fuzzy Architecture For Cmos Implementation
Abstract
In this paper, a nonconventional structure for a "fuzzy" controller is proposed, It does not require signal division, and it produces control surfaces similar to classical fuzzy controllers. The structure combines fuzzification, MIN operators, normalization, and weighted sum blocks. The fuzzy architecture is implemented as a VLSI chip using 2-mu m n-well technology. A new fuzzification circuit, which requires only one differential pair per membership function is proposed. Eight equally spaced membership functions are used in the VLSI implementation. Simple voltage MIN circuits are used for rule selection. A modified Takagi-Sugeno approach with normalization and weighted sum is used in the defuzzification circuit. Weights in the defuzzifier are digitally programmable with 6-bits resolution.
Year
DOI
Venue
1999
10.1109/41.808001
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Keywords
Field
DocType
control, fuzzy, VLSI
Fuzzy electronics,Neuro-fuzzy,Defuzzification,Control theory,Fuzzy logic,Control engineering,Fuzzy set,Fuzzy associative matrix,Fuzzy number,Membership function,Mathematics
Journal
Volume
Issue
ISSN
46
6
0278-0046
Citations 
PageRank 
References 
14
1.35
7
Authors
3
Name
Order
Citations
PageRank
Bogdan Wilamowski150838.07
Richard C. Jaeger2519.34
M. Okyay Kaynak32378178.15