An Optimal TSK Fuzzy Neural Network Controller without Using the Error Change Rate Information
碩士 === 中原大學 === 電機工程研究所 === 90 === This thesis proposes an optimal FNNC whose initial setting of parameters and learning rate are done by AGA. The FNNC is based on TSK fuzzy model and is realized from the network point of view. The parameters of the fuzzy model are tuned on-line by a backpropogatio...
Main Authors: | Ruey-Chuan Lu, 呂瑞權 |
---|---|
Other Authors: | Lin-Ying Lai |
Format: | Others |
Language: | zh-TW |
Published: |
2002
|
Online Access: | http://ndltd.ncl.edu.tw/handle/99899543911075247802 |
Similar Items
-
tsk tsk tsk and Beyond: Anticipating Distributed Aesthetics
by: Darren Tofts
Published: (2005-01-01) -
TSK model design for multistage fuzzy controllers
by: 李文同
Published: (2002) -
PARAMETERS ESTIMATION OF PID CONTROLLER USING TSK-TYPE RECURRENT FUZZY NEURAL NETWORK
by: Chang-Hung Liu, et al.
Published: (2012) -
Evolutionary Algorithms Based on TSK-Type Neural Fuzzy System with Applications to Medical Images
by: Chen, Hsien Tse, et al.
Published: (2013) -
Using Particle Swarm Optimization to Improve TSK Fuzzy Model for Function Approximation
by: I-Lin Lee, et al.
Published: (2008)