DocumentCode :
2294096
Title :
The Direct Inverse-Model Control Based on Neural Networks for Inverts
Author :
Wang Ping ; Cheng Baohua ; Xing Wenchao ; Ding Hui
Author_Institution :
Tianjin Univ., Tianjin, China
Volume :
3
fYear :
2010
fDate :
13-14 March 2010
Firstpage :
855
Lastpage :
858
Abstract :
This paper proposed the inverse model control strategy of the inverter in the field of active power filter. Since the inverse model of the inverter can not be easily as well as accurately obtained, BP neural network is introduced to approach the inverse model. After the training of the neural network, we can connect it with the inverter to get a nearly ideal linear system. Various simulations are done under different conditions to prove this method to be effective. Finally an active power filter system is simulated, the result proved to be favorable.
Keywords :
backpropagation; invertors; neurocontrollers; power filters; BP neural network; active power filter; direct inverse model control; ideal linear system; neural networks; Active filters; Automatic control; Circuit simulation; Control systems; Inverse problems; Mathematical model; Neural networks; Power harmonic filters; Power system modeling; Pulse width modulation inverters; Active power filter; Inverse model control; Inverter; Neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Conference_Location :
Changsha City
Print_ISBN :
978-1-4244-5001-5
Electronic_ISBN :
978-1-4244-5739-7
Type :
conf
DOI :
10.1109/ICMTMA.2010.289
Filename :
5459503
Link To Document :
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