Fuzzy-Neural Network Control Algorithm and the
Application in Centrifugal Force and
Vibration Combined Environment Testing System
Liu Bing    Cheng Weiguo     Yan Guirong
(Xi'an Jiaotong University, Xi'an 710049)
Niu Baoliang    Li Ronglin
(China Academy of Engineering Physics)

Abstract: A new adaptive control method based on fuzzy-neural network, with respect of the complex nonlinearities and coupling in the centrifugal force and vibration combined environment testing system, is presented and a controller based fuzzy-neural reasoning is designed in this paper. A controller is composed of the fuzzy controller and FNI network. The control-rules is produced by fuzzy controller. FNI network is trained off-line by steepest gradient drop algorithm, the samples for training FNI regulated on-line by using the measured input/output data with the neural network learning method derived from steepest gradient drop algorithm. The output of network is mapped the input of vibrator by compressor. The effectiveness of the tracking control system is verified by experiment results.
Keywords: centrifugal force, vibration, fuzzy control, neural network.