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- W2370599680 abstract "A model predictive control strategy based on neural network is presented for a continuous stirred tank reactor(CSTR).A segmentation method was adopted to identify Hammerstein-Wiener model coefficient by least squares support vector machines and then to construct a nonlinear predictive controller which was by a linear optimal component and radial basis function neural networks in series.A nonlinear predictive control algorithm based on least support vector machines Hammerstein-Wiener model was realized by using BP neural network to train predictive input sequences and to solve nonlinear predictive control rules by Quasi-Newton method.The simulation results of CSTR illustrate that this approach is effective tracking and controlling product concentration." @default.
- W2370599680 created "2016-06-24" @default.
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- W2370599680 date "2011-01-01" @default.
- W2370599680 modified "2023-09-23" @default.
- W2370599680 title "Neural network predictive control of continuous stirred-tank reactor based on Hammerstein-Wiener model" @default.
- W2370599680 hasPublicationYear "2011" @default.
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