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A predictive control method based on neural network is presented for the problem of production inconvenience and low precision in a continuous stirred tank reactor(CSTR) which is widely used in chemical process. Firstly, using a multi-layer feed forward neural network to approximate the CSTR system’s multi-step predictive value, secondly based on the forecast model for solving quadratic objective function optimization predictive control by the Taylor expansion approximation quadratic nonlinear predictive control law controller. The simulation results of CSTR show that :that essay’s method has high accuracy and that method is feasible and effective. The utility model has the advantages of high production efficiency, high product quality and high practical value.