Simulation and application of magnesium alloy gap controller based on hybrid prediction model

The gap control system of magnesium alloy strip is characterized by nonlinear structure, time-varying parameters and large hysteresis. It is difficult to obtain satisfactory control effect by conventional control methods. This paper puts forward a kind of hybrid prediction optimization algorithm based on the grey prediction model GM(1, 1), combined with the advantages of the rolling optimization strategy. It overcomes the grey forecasting model dimension and effect of prediction step, gets more accurate dynamic rolling forecast data, makes up for the weakness of the thickness actuator and the lag of the detection mechanism. Furthermore, it uses Smith Prediction to replace in the steady-state rolling, so as to avoid the inaccuracy of the prediction value obtained by Gray Prediction Model entering after the steady state. This optimized algorithm not only makes up for the defects of the Gray Prediction Model, but also improves the accuracy of the prediction data. It can effectively improve the dynamic thickness and accuracy control through the field rolling.