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Neural Network Inverse Adaptive Controller Based or,Davidon Least Square*
/ L# C3 U( [0 X5 M6 RChen Zengqiang, Lu Zhao & Yuan Zhtuzhi 9 }( i. J9 U( ?! E0 H, p
Department of Computer & System Science, Nankai Univeraity, Tianjin, 300071, P. R. China 0 I5 J3 p+ h I. G- O9 [: J
(Received September 20, 1999) 9 \( M" `! j5 N& |4 ] I
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Abstract: General neural network inverse adaptive controller haw two flaws: the first i the slow convergence speed; the second is the invalidation to the non-minimum phase mystem. Tbese defects limit the scope in which the neural network inverse adaptive controller is used. We employ Davidon least squares in training the multi-layer feedforward neural network used in approximating the invense model of plant to expedite the convergence, and then through constructing the pseudo-plant, a neural network inverse adaptive controller泅put forward which is stil efective to the nonlinear non-minimum phase system. The simulation reoults show the validity of this scheme.
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Keywords: Neural network, Adaptive control, Davidon least squarea, Inverse control.0 h, r1 O6 o8 Q! R+ K' d
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