Adaptive Learning of Rolling Force Model Based on Adaptive Genetic Algorithm in Tandem Cold Rolling

To improve the precision of rolling force model in tandem cold rolling,the Bland-Ford-Hill model was used for rolling force model in which the plastic deformation in bite zone and elastic deformation at entry and exit of bite zone were considered.Aiming at the actual precision of the rolling force,an improved adaptive genetic algorithm was proposed in order to search the deformation resistance and the friction coefficient.Further, the adaptive learning coefficient of the deformation resistance and the friction coefficient could be obtained by way of exponential smoothing average.The experiment results showed that the accuracy of the actual value of rolling force could meet the requirement of on-line process control.