Title :
Study on the Energy Saving of Mine Ventilator Based on Artificial Intelligence Control System
Author :
Xinhui Du ; Song, Jiancheng ; Zhu, Shanjun
Author_Institution :
Coll. of Electr. & Power Eng., Taiyuan Univ. of Technol., Taiyuan, China
Abstract :
Radial Basis Function(RBF) is used to identify the model of mine ventilator, frequency control system is introduced to control the speed of ventilator, and traditional control strategy used PID is replaced by FNN. The MATLAB simulation results show that the ventilator modeling by RBF neural network can better reflect its nonlinear characteristic, the speed of ventilator controlled by FNN changed with the gas´s concentration. The paper take a mine of Shanxi for example to calculate the energy saving index, the result reveals it has produced not only direct economic benefit but also great social and environmental benefit.
Keywords :
frequency control; mining; neurocontrollers; radial basis function networks; velocity control; ventilation; RBF neural network; artificial intelligence control system; energy saving; frequency control system; mine ventilator; radial basis function network; ventilator speed; Artificial neural networks; Biological system modeling; Control systems; Fuel processing industries; Fuzzy control; MATLAB; Mathematical model; FNN control; energy saving; mine ventilator; radial neural network;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6880-5
DOI :
10.1109/iCECE.2010.530
