A Fuzzy Adaptive Control Theory Based Study On Zinc Coating Thickness Predictive Control

With the development of automobile and house appliance industries,the social demand for galvanized products increased significantly.Companies can improve the quality of galvanized products and thus reduce production costs by precisely controlling the thickness of Zinc coating according to customer needs.At present,all advanced hot-dip galvanizing produce lines in China are imported from foreign countries.Therefore,it is of practical significance to carry out studies on Zinc coating thickness control on strip steel surface and thus to improve China's independent intellectual property rights and develop Chinese own Zinc coating thickness control system.The present thesis first conducts an in-depth research on zinc coating thickness control system in hot-dip galvanizing line,which includes preset control,lateral error control and longitudinal average control of Zinc coating thickness.The preset control of Zinc coating thickness is computed by setting the value of these main controlling quantities.The lateral error control of Zinc coating thickness is achieved by improving the lateral evenness of the coating after controlling the size of the lip gap of air knife.The average longitudinal thickness control is completed through increasing the preciseness of the coating's average longitudinal thickness after adjusting the air pressure of air knife and the distance between strip and air knife.By doing the quantitative analysis of the key factors which determine the zinc layer thickness,this thesis establishes a zinc layer thickness regression model.And choosing the least square method as the method to estimate and solve the model parameters in this thesis.After the examination,the thesis gets the result that the zinc layer thickness model has a higher goodness of fit and a lower error indicator than the mechanism model.Through the relevant analysis,there is a higher relevance between the strip speed and the height of the air knife.The partial least square method using the single dependent variable obtains a new regression model parameter.Hot dip galvanizing is a nonlinear process with multi-variables and big time lags.In China,most galvanized production lines still applies the traditional PID controller to control the thickness of strip steel's Zinc coating.However,with interfering factors at site and time lags happening in the controlling process,this traditional control method will inevitably reduce the effect of Zinc coating thickness control.To solve the problem of time lag,the present study strives to enhance adaptive capacity of conventional fuzzy controller,taking fuzzy predictive control system as the main control strategy and applying self-tunning factor fuzzy predictive control.Based on fuzzy adaptive theory,the study,starting from adjusting pressure,also works out a Zinc coating thickness predictive controller under the condition when air knife jet pressure is not saturated.The simulation results show that,he fuzzy adaptive predictive controller outperform the traditional PID controller with shorter adjusting time,smaller overshoot,stronger robustness to optimize the control outcome of the original system and improve the Zinc coating's quality on the strip steel surface.