Research On Intelligent Control Of Hot Rolled Strip Thickness

Hot rolled strip is widely used in various sectors of the national economy, and the strip thickness is an important index to measure the quality of hot strip, the prediction and control of hot rolled strip thickness is the theoretical basis for this technology.In this paper, through the control of hot rolled strip thickness, Due to the plate thickness control process is a typical nonlinear, large delay, time-varying, in the application of conventional PID control, it is often difficult to deal with complex nonlinear control system. In this paper, through the establishment of expert fuzzy controller, strip thickness control of1500hot rolling plate, and show that the MATLAB simulation, not only improve the accuracy, the dynamic and steady state performance of the system, but also enhance the robustness of the system, as the expert fuzzy control in hot strip thickness control provides a new available some application examples.For predicting the hot-rolled strip thickness, this paper proposed for an improved GA and neural network model which has good global search ability, it improved not only the speed of convergence but also accuracy of the network. In the application of hot-rolled strip thickness prediction, this model overcomes the shortcomings of the traditional model’s lower precision and easier to fall into the local minimum problem, effectively improved the prediction of strip thickness, provided better guarantee to strip thickness control.