DocumentCode :
2153467
Title :
Fault test of networked synchronization control system by the combination of RBF neural network and particle swarm optimization
Author :
Wang Ting ; Wang Heng ; Hao-fei, Xie
Author_Institution :
Key Lab. of Network Control & Intell. Instrum., Chongqing Univ. of Posts & Telecommun., Chongqing, China
Volume :
3
fYear :
2010
fDate :
26-28 Feb. 2010
Firstpage :
383
Lastpage :
386
Abstract :
Networked synchronization control has very high technology level, which includes network technology and synchronization control technology, etc. Fault diagnosis of the devices in networked synchronization control system has a great importance for ensuring the normal operation. The radial basis function neural network with particle swarm optimization algorithm is developed. The combination method of RBF neural network and particle swarm optimization is applied to fault diagnosis of networked synchronization control system. The test results indicate that the combination model of RBF neural network and particle swarm optimization can almost entirely recognize each state of the device in networked synchronization control system. The diagnostic accuracy of the combination model of RBF neural network and particle swarm optimization is greater than that of normal RBF neural network.
Keywords :
control systems; fault diagnosis; neurocontrollers; particle swarm optimisation; radial basis function networks; synchronisation; RBF neural network; diagnostic accuracy; fault diagnosis; fault test; network technology; networked synchronization control system; particle swarm optimization; radial basis function neural network; Control systems; Fault diagnosis; Instruments; Intelligent control; Intelligent networks; Laboratories; Neural networks; Particle swarm optimization; System testing; Telecommunication control; fault test; networked synchronization control system; neural network; particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-5585-0
Electronic_ISBN :
978-1-4244-5586-7
Type :
conf
DOI :
10.1109/ICCAE.2010.5451386
Filename :
5451386
Link To Document :
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