scholarly journals Wind Turbine Driving a PM Synchronous Generator Using Novel Recurrent Chebyshev Neural Network Control with the Ideal Learning Rate

Energies ◽  
2016 ◽  
Vol 9 (6) ◽  
pp. 441 ◽  
Author(s):  
Chih-Hong Lin
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Synchronous Generator ◽  
Network Control ◽  
Learning Rate ◽  
Neural Network Control ◽  
Chebyshev Neural Network ◽  
The Ideal

scholarly journals Novel Modified Elman Neural Network Control for PMSG System Based on Wind Turbine Emulator

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Chih-Hong Lin
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Permanent Magnet ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Generator ◽  
Power Converter ◽  
Network Control ◽  
Elman Neural Network ◽  
Wind Speeds ◽  
Ac Power

The novel modified Elman neural network (NN) controlled permanent magnet synchronous generator (PMSG) system, which is directly driven by a permanent magnet synchronous motor (PMSM) based on wind turbine emulator, is proposed to control output of rectifier (AC/DC power converter) and inverter (DC/AC power converter) in this study. First, a closed loop PMSM drive control based on wind turbine emulator is designed to generate power for the PMSG system according to different wind speeds. Then, the rotor speed of the PMSG, the voltage, and current of the power converter are detected simultaneously to yield better power output of the converter. Because the PMSG system is the nonlinear and time-varying system, two sets online trained modified Elman NN controllers are developed for the tracking controllers of DC bus power and AC power to improve output performance of rectifier and inverter. Finally, experimental results are verified to show the effectiveness of the proposed control scheme.

The Summary of Tunnel Boring Machine Control Based on the Neural Network

2013 ◽  
Vol 706-708 ◽  
pp. 1090-1093
Author(s):  
Jin Zhi Liu ◽  
Jun Lin ◽  
Li Ming Ma ◽  
Shen Shan Li
Keyword(s):  
Neural Network ◽  
Intelligent Control ◽  
Tunnel Boring Machine ◽  
Network Control ◽  
Neural Network Control ◽  
Tunnel Boring ◽  
Process Uncertainty ◽  
The Neural Network ◽  
Machine Control ◽  
The Ideal

Conventional control of tunnel boring machine can't achieve the ideal effect because of the complexity of its work process, uncertainty of construction environment. In order to solve the question, the intelligent control is expected. The neural network control has many characteristics such as self-adaption, self-organization, and can modify the corresponding parameters by learning about external knowledge, so it becomes research focus of tunnel boring machine control system in recent years. In this paper the advantage and disadvantage of several kinds of neural network used in the tunnel boring machine control are introduced, the development trends of tunnel boring machine control is predicted.

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