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An improved Elman neural network, the hybrid feedback Elman neural network is presented for the modeling of unknown delay and high-order nonlinear system. The stability of the improved Elman network is proved in the sense of Lyapunov stability theory, and then chaos searching is imported to train it, make BP algorithm can skip the local minimum and find the global minimum easily. Modeling and prediction...
An efficient implementation of generalized predictive control using multi-layer feed forward neural network as the plantpsilas nonlinear model is presented. Two algorithm i.e. Newton Raphson and Levenberg Marquardt algorithm are implemented and their results are compared. The details about this implementation are given. The utility of each algorithm is outlined in the conclusion. In using Levenberg...
In order to improve the global convergence of the basic particle swarm optimization, an adaptive expanded particle swarm optimization method was provided in this paper firstly, where particle is refreshed by multi-particle strategy; at the same time, the parameter c0 is self-adaptively adjusted. Then improved PSO was used as the optimizer of the neural network predictive control and optimized the...
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