PID Parameter Tuning And The Sliding Mode Controller Design On Laminar Cooling Control System

With the development of production and social progress, the demand of steel variety and quality becomes increasing important in the market. The strip coiling temperature of hot rolling is a key factor in product quality, and its direct impact on the control precision strip of tissue and mechanical properties. Coiling temperature is too high and too low will cause a serious decline in the quality of the coil, so improve the control precision of coiling temperature has an important significance. In this paper,2300mm hot strip rolling of Benxi Iron Steel unit as the background, with its laminar cooling system as the research object, the system’s process and control systems were studied.In order to learn more about the laminar cooling system in hot rolling strip steel, this paper studied about the process of the cooling system, and had a better understand about the mathematical model, on-site mechanical and electrical equipment of the system. Meanwhile digest and absorb the control system of it, The control strategy of the strip laminar cooling control system is to strip subsection control, based on the data, the system constitutes by export preset, feed-forward and feedback control. Pre-set strip cooling model calculates the required coiling temperature during the process, feed-forward control would revise the pre-set control, the feedback control adjust the water flues based on the actual temperature. Finally, the paper had a deep research about the control system. The laminar cooling control system is a time-delay system. Its controlled object is a big lag, and the laminar cooling process is a complex non-linear which makes us difficult to obtain precise mathematical model and cannot adjust with the conventional PID control.According to the defects about PID controller, this paper combine the fuzzy control and PID controller together to enhance the control accuracy. After continuous debugging and simulation found that when the Smith predictor parameters matches the controlled object parameters, this method effectively solve the long adjustment time caused by PID parameters does not match the controller, and reached the range of PID controller parameters and improved the efficiency of parameters adjustment. However when the Smith predictor parameters does not match the parameters of the controlled object, the system stability is not significantly improved. As we know sliding mode controller has a fast response, insensitive to the parameter changes and external disturbance and has a better control about the time-delay system, this paper designs a sliding mode controller to optimize the system. Through simulation, this control is better than the fuzzy PID control, and the drawback is that there is buffeting in the system. Finally, calculating with the on-site data according to the process, from the coiling temperature control curve we can found that the coiling temperature control range of the target coiling temperature can meet the engineering needs, and can be applied in practical engineering.