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An adaptive neural control method is presented for the nonlinear discrete-time systems with the NARMA-L2 model. The neural fuzzy system is integrated with the approximate model-based control method to handle the nonlinear complexity, where the multiple fuzzy CMAC (MFCMAC) network is used to compensate the approximate NARMA model of the nonaffine nonlinear system. The weights of neural networks are...
Based on neural networks, an adaptive control design method was proposed for a class of uncertain block nonaffine system. This problem is considered difficult to be dealt with in the control literature, mainly because that the virtual controls of block nonaffine system are not easy to resolve. To overcome this difficulty, the RBF neural network (NN) was used to approximate and adaptively cancel the...
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