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Hybrid supervisory control using recurrent fuzzy neural network for tracking periodic inputs
Faa Jeng Lin
, Rong Jong Wai
, Chun Ming Hong
電機工程學系
研究成果
:
雜誌貢獻
›
期刊論文
›
同行評審
64
引文 斯高帕斯（Scopus）
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Keyphrases
Periodic Input
100%
Recurrent Fuzzy Neural Network
100%
Hybrid Supervisory Control
100%
Control Law
57%
Supervisory Control System
57%
Permanent Magnet Linear Synchronous Motor (PMLSM)
42%
Intelligent Control System
42%
System State
28%
Control Effort
28%
Mover
28%
Periodic Reference
28%
Reference Input
28%
Supervisory Control
28%
Fuzzy Neural Network Control
28%
Servo Drive
14%
Servo Motor
14%
Control System
14%
Control Performance
14%
Learnability
14%
Lyapunov Stability Theorem
14%
Fast Convergence
14%
Dynamic Equations
14%
Periodic Motion
14%
Robust Control
14%
Uncertainty Bounds
14%
Gradient Method
14%
Fuzzy Inference
14%
Compensating Controls
14%
Field-oriented
14%
Dynamic Mapping
14%
Chatter Control
14%
Tracking Controller
14%
On-line Parameters
14%
Training Methodology
14%
Parameter Training
14%
Engineering
Control System
100%
Recurrent
100%
Supervisory Control
100%
Control Law
57%
Synchronous Motor
42%
Permanent Magnet
42%
System State
28%
Reference Input
28%
Lyapunov Stability Theorem
14%
Periodic Motion
14%
Convergence Speed
14%
Fuzzy Inference
14%
Gradient Descent Method
14%
Servomotors
14%
Computer Science
Fuzzy Recurrent Neural Network
100%
Permanent Magnet
60%
Intelligent Control System
60%
Network Control
40%
Fuzzy-Neural System
40%
Reference Input
40%
Lyapunov Stability
20%
Fast Convergence
20%
Dynamic Equation
20%
Convergence Speed
20%
Gradient Descent Method
20%
Dynamic Mapping
20%
Controlled System
20%
Periodic Motion
20%
Chemical Engineering
Fuzzy Neural Networks
100%