TY - JOUR
T1 - An adaptive fuzzy logic controller
T2 - Its VLSI architecture and applications
AU - Jou, Jer Min
AU - Chen, Pei Yin
AU - Yang, Sheng Fu
N1 - Funding Information:
Manuscript received August 11, 1998; revised December 26, 1998. This work was supported in part by the National Science Council, R.O.C., under Grant NSC-84-2215-E-006-025. J. M. Jou and S.-F. Yang are with the Department of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan, R.O.C. P.-Y. Chen is with the Department of Electronic Engineering, Southern Taiwan University of Technology, Tainan 710, Taiwan, R.O.C. Publisher Item Identifier S 1063-8210(00)00002-0.
PY - 2000
Y1 - 2000
N2 - Most previous work about the hardware design of a fuzzy logic controller (FLC) intended to either improve its inference performance for real-time applications or to reduce its hardware cost. To our knowledge, there has been no attempt to design a hardware FLC that can perform an adaptive fuzzy inference for the applications of on-line adaptation. The purpose of this paper is to present such an adaptive memory-efficient FLC and its applications. Taking advantage of the adaptability provided by a symbolic fuzzy rule format and the dynamic membership function generator, as well as the high-speed integration capability afforded by VLSI, the proposed adaptive fuzzy logic controller (AFLC) can perform an adaptive fuzzy inference process using various inference parameters, such as the shape and location of a membership function, dynamically and quickly. Three examples are used to illustrate its applications, and the experimental results show the excellent adaptability provided by AFLC.
AB - Most previous work about the hardware design of a fuzzy logic controller (FLC) intended to either improve its inference performance for real-time applications or to reduce its hardware cost. To our knowledge, there has been no attempt to design a hardware FLC that can perform an adaptive fuzzy inference for the applications of on-line adaptation. The purpose of this paper is to present such an adaptive memory-efficient FLC and its applications. Taking advantage of the adaptability provided by a symbolic fuzzy rule format and the dynamic membership function generator, as well as the high-speed integration capability afforded by VLSI, the proposed adaptive fuzzy logic controller (AFLC) can perform an adaptive fuzzy inference process using various inference parameters, such as the shape and location of a membership function, dynamically and quickly. Three examples are used to illustrate its applications, and the experimental results show the excellent adaptability provided by AFLC.
UR - http://www.scopus.com/inward/record.url?scp=0034135702&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0034135702&partnerID=8YFLogxK
U2 - 10.1109/92.820761
DO - 10.1109/92.820761
M3 - Article
AN - SCOPUS:0034135702
SN - 1063-8210
VL - 8
SP - 52
EP - 60
JO - IEEE Transactions on Very Large Scale Integration (VLSI) Systems
JF - IEEE Transactions on Very Large Scale Integration (VLSI) Systems
IS - 1
ER -