NN adaptive pole placement method for sintering finish point control

Li Peng, Qing Li, Wen Li, and Shufen LiInformation Engineering School, University of Science and Technology Beijing, Beijing 100083, ChinaHebei Polytechnic University, Tangshan 063009, ChinaBeijing Union University, Beijing 100101, China

摘 要：<正> A neural network model with a special structure, which is divided into linear and nonlinear parts, was proposed for identification of a nonlinear system. In this model, the nonlinear part of the object is treated as a measured disturbance, and is compensated by a feed forward method; an adaptive pole placement algorithm is used to control the linear part of the object. The simulation results show that the identification efficiency and accuracy are improved when the new controller is applied to sintering finish point control.

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