Title :
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
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;
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
DOI :
10.1109/BICTA.2010.5645081