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Gao Pu
School of Mechatronics,
Lanzhou Jiaotong University,
Lanzhou 730070, China
Li Yunhua
School of Automation Control,
Beijing University of Aeronautics
and Astronautics,
Beijing 100083, China
Sheng Wanxing
China Electric
Power Research Institute,
Beijing 100085, China |
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FUZZY NEURAL NETWORK CONTROL FOR VIBRATION WAVEFORM SYSTEM OF
MOLD*
Abstract: Combining with the characteristic of the fuzzy control and the neural network control(NNC), a new kind of the fuzzy neural network controller is proposed, and the synthesis design method of the control law and fast speed learning algorithm of the parameters of networks are put forward. The output of the controller is composed of two parts, part one is derived on basis of the principle of sliding control, the lower order model and the estimated parameters of the plant are only required, part two is derived on basis FNN, it is used to compensate the uncertainties of the systems. Because new type of FNN controller extracts from the advantages of the intelligent control and model based sliding mode control, the numbers of adjusting parameters and the structure of FNN are simplified at large, and the practical significance and variation range are attached to each layer of the network and its connected weights, the control performance and learning speed are increased at large. The rightness of the conclusions is verified by the experiment of an electro-hydraulic position servo system of the mold of the continuous casting machinery.
Key words:
Fuzzy control Neural networks Sliding mode control Electro-hydraulic servo system |