DocumentCode :
2399853
Title :
A PID Control Algorithm for Wood Drying Mmachine Based on RBF Neural Network
Author :
Chen, Long ; Ren, Hong-E
Author_Institution :
Inf. & Comput. Eng. Coll., Northeast Forestry Univ., Harbin, China
Volume :
2
fYear :
2010
fDate :
26-28 Aug. 2010
Firstpage :
224
Lastpage :
227
Abstract :
The control problem of Wood Vacuum Dehumidifier is very complicated. A PID control method based on RBF neural network algorithm is designed. The controller is based on the conventional PID control, . makes use of the study ability of the nerve network to turning the PID control parameters, and proceeds the simulation research using matlab software. From the simulation results, it is can be shown that Neural Network PID controller have the higher accuracy and stronger adaptability, and can get satisfied control result.
Keywords :
drying; humidity control; neural nets; neurocontrollers; production equipment; radial basis function networks; three-term control; wood; Matlab; PID control; RBF neural network; wood drying machine; wood vacuum dehumidifier; Adaptation model; Algorithm design and analysis; Artificial neural networks; Resistance heating; Temperature measurement; Tuning; MATLAB; PID; radial basis function neural network; vacuum dehumidify drier;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2010 2nd International Conference on
Conference_Location :
Nanjing, Jiangsu
Print_ISBN :
978-1-4244-7869-9
Type :
conf
DOI :
10.1109/IHMSC.2010.156
Filename :
5590823
Link To Document :
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