Title :
A novel hysteresis current control strategy based on neural network
Author :
Dazhi, Wang ; Guoqing, Ji ; Jun, Li ; Hualong, Sun ; Shengli, Liu ; Keling, Song
Author_Institution :
Inst. of Electr. Power Syst. & Motor Drives, Northeastern Univ., Shenyang, China
Abstract :
The relationship among principle of variable-band hysteresis current control, compensation capacity of hysteresis and switching frequency is dissertated in this paper. Aimed at changing the disadvantages of variable-band current control strategy resulted from the fuzzy controller, a control strategy based on command current and current error is proposed and realized by neural network. Power electronics model is built by MATLAB and PSIM and logical control circuit is built according to the fuzzy rules and neural network respectively. Co-simulation results indicate that the hysteresis based on neural network controller has better compensation capacity than the hysteresis based on fuzzy controller and reduces switching frequency.
Keywords :
electric current control; hysteresis; logic circuits; neurocontrollers; power filters; switching convertors; MATLAB; PSIM; active power filter; compensation capacity; fuzzy rules; logical control circuit; neural network controller; power electronics model; switching frequency; variable-band hysteresis current control; Current control; Electric variables control; Error correction; Fuzzy control; Fuzzy neural networks; Hysteresis; Mathematical model; Neural networks; Power electronics; Switching frequency; active power filter; co-simulation; hysteresis current control; neural network;
Conference_Titel :
Computer Design and Applications (ICCDA), 2010 International Conference on
Conference_Location :
Qinhuangdao
Print_ISBN :
978-1-4244-7164-5
Electronic_ISBN :
978-1-4244-7164-5
DOI :
10.1109/ICCDA.2010.5541502
