Title :
Self-Recovery of Motor Control Circuit Based on MFNNVRC
Author :
Jie, Chu ; Hua, Man Meng ; Shang-he, Liu ; Miang, Wei ; Liang, Yuan ; Quan, Ju Zheng ; Xiao-long, Chang
Author_Institution :
Inst. of Electrostatic & Electromagn. Protection, Mech. Eng. Coll., Shijiazhuang, China
Abstract :
To solve the problems of the unknown of ordinary FPGA configuration bitstreams and long time for download configuration bitstreams into ordinary FPGA in evolvable hardware, multilayer feed forward neural network was combined with virtual reconfigurable circuit to build MFNNVRC in an ordinary FPGA. This MFNNVRC structure was used to implement the control circuit of three phase brushless DC motor. In order to validate the effectiveness of this circuit design, a self-recovery experiment was carried out in the FPGA with some given partial faults. The successful result of experiment argues that the proposed circuit is a befitting evolutionary reconfigurable platform utilizing ordinary FPGAs for combinational logic circuits.
Keywords :
brushless DC motors; combinational circuits; field programmable gate arrays; logic design; machine control; multilayer perceptrons; neurocontrollers; reconfigurable architectures; MFNNVRC structure; circuit design; combinational logic circuits; download configuration bitstreams; evolutionary reconfigurable platform; motor control circuit self-recovery; multilayer feed forward neural network; ordinary FPGA configuration bitstreams; three phase brushless DC motor; virtual reconfigurable circuit; Circuit faults; Electrostatics; Feedforward neural networks; Field programmable gate arrays; Motor drives; Multiplexing; Registers; Evolvable hardware; Field programmable gate array; Multilayer feedforward neural network; Self-recovery; Virtual reconfigurable circuit;
Conference_Titel :
Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4673-1450-3
DOI :
10.1109/ICICEE.2012.501