Title :
The third kind of generalized congruence neural network is used to diagnose fault of attitude control system
Author :
Xu Yangmin ; Xue Lei ; Wang Keren ; Xu Jiren ; Liu Jihai
Author_Institution :
Dept. of Inf., Electr. Eng. Inst. of Hefei, Hefei, China
Abstract :
This paper uses generalized congruence function instead of transfer function of classical BP neural network, and improve convergence rate of neural network. We introduce the subsection generalized derivation, error back propagation derivation mechanism of classical BP algorithm to adjust weight vector in generalized congruence neural network, and modify generalized congruence neural network, and then can obtain the third kind of generalized congruence neural network (GCNN3). Finally, by means of fault diagnosis experiment of attitude control system, we compare approximation performance of the third kind of generalized congruence neural network with BP neural network; approximation effect and stable performance of GCNN3 is equivalent to BPNN, but convergence rate of the former is much faster than the latter.
Keywords :
attitude control; backpropagation; convergence; fault diagnosis; neural nets; transfer functions; BP neural network; attitude control system; error back propagation derivation mechanism; fault diagnosis; generalized congruence neural network; transfer function; Artificial neural networks; Attitude control; Fault diagnosis; Neurons; Training; Transfer functions; Underwater vehicles; Fault diagnosis; Neural network; generalized congruence;
Conference_Titel :
Computer Research and Development (ICCRD), 2011 3rd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-839-6
DOI :
10.1109/ICCRD.2011.5764148