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- W2364195339 abstract "The work presented here aims establishing the self-adaptive PID neural network control on the basis of the combination of the identification network of the RBF neural network and the controller of the BP neural network. RBF neural network adopts the off-line training and the on-line adaptation of weight and threshold value. In order to speed up the convergence, the grads descent method with inertia item was used. Massive stimulation proves the superiority of the RBF network to the ELM and the standard and the ameliorated BP. Stimulation to the pilotless aircraft turbojet engine proves several advantages of this controlling method, such as good robustness, sensitive response, and minimal stable error." @default.
- W2364195339 created "2016-06-24" @default.
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- W2364195339 date "2003-01-01" @default.
- W2364195339 modified "2023-09-22" @default.
- W2364195339 title "Neural network PID adaptive control in pilotless aircraft turbojet engine" @default.
- W2364195339 hasPublicationYear "2003" @default.
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