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Aimed at the difficulty of nonlinear system control, take advantage of the high exactitude approaching ability of RBF neural network to nonlinear system, a model identification method based on neural network is formed. At the same time, use the single-neuron Net to construct an auto-adaptive PID controller. Combine them, a new control method appear. The result of the simulation indicated that the...
A DFOPDT model of nonlinear temperature system with time-delay is established. An algorithm is presented, which is an effective way to solve unknown parameters of the model by neural network. In the method, the network can soon converge through the iterative calculation in which the value of unknown parameters is predicted continuously. Meanwhile, it also solves to train a network with unknown output...
Considering the difficulty of large time-delay process control, take advantage of the approaching ability of neural network to nonlinear system, a smith predictor with neural network is constructed. At the same time, use identification-free adaptive algorithm to adjust the coefficient of the single-neuron PSD controller. Combine them, a new control method appear. The result of the simulation indicated...
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