RADIAL BASIS FUNCTION NETWORK BASED AUTOMATIC GENERATION FUZZY NEURAL NETWORK CONTROLLER FOR PERMANENT MAGNET LINEAR SYNCHRONOUSMOTOR
碩士 === 大同大學 === 電機工程學系(所) === 95 === In this thesis, a radial basis function network (RBFN) based automatic generation fuzzy neural network (AGFNN) is proposed to control the rotor position of the permanent magnet linear synchronous motor (PMLSM) to track the period reference trajectories. The propo...
Main Authors: | Wen-Yen Hsu, 徐文彥 |
---|---|
Other Authors: | Hung-Ching Lu |
Format: | Others |
Language: | en_US |
Published: |
2007
|
Online Access: | http://ndltd.ncl.edu.tw/handle/8u99fa |
Similar Items
-
AUTOMATIC GENERATION FUZZY NEURAL NETWORK CONTROLLER WITH SUPERVISORY CONTROL FOR PERMANENT MAGNET LINEAR SYNCHRONOUS MOTOR
by: Yao-Hua Ke, et al.
Published: (2007) -
Hardware radial basis function neural network automatic generation
by: Lucas Leiva, et al.
Published: (2011-04-01) -
The Fuzzy Neural Network Variable Structure System Controller of Permanent Magnet Linear Synchronous Motor
by: Hsi-Chen Liu, et al.
Published: (2008) -
The Study of Fuzzy-Neural Network for a Permanent Magnet Synchronous Motor Drive
by: Chen-Wen Chang, et al.
Published: (2011) -
Decoupling control of a five-phase fault-tolerant permanent magnet motor by radial basis function neural network inverse
by: Qian Chen, et al.
Published: (2018-05-01)