ANN based three-value logic SVPWM control in CSR

Author

Xu, Jinbang ; Anwen Shen ; Wu, Zhizhuo ; Yang, Jun ; Yang, Xuan

Author_Institution

Dept. of Control Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China

fYear

2010

fDate

23-26 Sept. 2010

Firstpage

1273

Lastpage

1277

Abstract

To achieve better performance with various load and system parameters in controlling a current-source rectifier (CSR) with less computing cost, a neural-network-based implementation of three-logic space-vector modulation (SVM) is proposed in this research, and the random weight change (RWC)algorithm is employed for on-line parameter tuning. The scheme has been simulated in SABER simulation software and the result is compared with the conventional SVM method. The advantage of the method is explicit with a better performance under a non-rated system load.

Keywords

PWM rectifiers; constant current sources; electrical engineering computing; logic circuits; neural nets; rectifiers; three-term control; vectors; ANN; CSR; SABER simulation software; current source rectifier control; online parameter tuning; random weight change algorithm; space vector modulation; three value logic SVPWM control; Artificial neural networks; Computational modeling; Support vector machines; CSR; RWC; neural-network; three value logic SVM;

fLanguage

English

Publisher

ieee

Conference_Titel

Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on

Conference_Location

Changsha

Print_ISBN

978-1-4244-6437-1

Type

conf

DOI

10.1109/BICTA.2010.5645081

Filename

5645081