DocumentCode :
3471463
Title :
Research on adjust speed control system of partial fan
Author :
Wang, Shufang ; Chen, Ruiyang ; Fang, Xin ; Wang, Jianbo
Author_Institution :
Beijing Union Univ., Beijing
fYear :
2007
fDate :
18-21 Aug. 2007
Firstpage :
1053
Lastpage :
1057
Abstract :
Combining with ventilation requirements and safety regulation in coalmine, control strategy which aims at both safety and energy saving is established at length. Moreover, conventional double fuzzy control model is found to carry out two work mode, normal ventilation and gas discharging. Since four input signals affect output in different degree, three layers BP neural network is employed to compute weight. Based on conventional fuzzy model, self learning fuzzy model for partial fan is build to tackle with normal ventilation and gas discharging problem. Direct torque control style is applied to perform speed adjusting of partial fan. In order to testify the control strategy, an experiment platform including DSP and IPM is founded. The experiment results show that the control strategy is effective to fulfill the function of ventilation and gas discharge in heading laneway.
Keywords :
adaptive control; backpropagation; coal; discharges (electric); fans; fuzzy control; neurocontrollers; self-adjusting systems; torque control; velocity control; ventilation; BP neural network; DSP; adjust speed control system; coalmine safety regulation; direct torque control; double fuzzy control model; gas discharging; normal ventilation; partial fan; safety-energy saving; self learning fuzzy model; ventilation requirements; Computer networks; Digital signal processing; Discharges; Fuzzy control; Neural networks; Safety; Testing; Torque control; Velocity control; Ventilation; DSP; gas discharging; heading laneway; self learning fuzzy control model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2007 IEEE International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-1531-1
Type :
conf
DOI :
10.1109/ICAL.2007.4338723
Filename :
4338723
Link To Document :
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