Command Filter-based Backstepping Control for the Speed and Tension System of the Reversible Cold Strip Rolling Mill Using Disturbance Observers

Abstract

This paper investigates the decoupling and coordinated tracking control problem for the speed and tension system of the reversible cold strip rolling mill. Using a diagonal matrix decoupling network and neural network disturbance observers, we propose a command filter-based backstepping control strategy. First, the diagonal matrix decoupling network is constructed to weaken the coupling between the speed and tension of the rolling mill system, which reduces the complexity of the system model effectively. Second, controllers are designed by combining the backstepping with the command filter, which solves the “explosion of complexity” problem in backstepping procedure, and optimizes the system’s control structure. Next, neural network disturbance observers are developed to observe the uncertain items of the system, which improve the tracking control precision of the system effectively. Theoretical analysis shows that all signals in the closed-loop system are uniformly ultimately bounded. Finally, simulation research is carried out on the speed and tension system of a 1422 mm reversible cold strip rolling mill; results show that using the proposed control strategy increased the dynamic response speed of the system by approximately 1s, and the stability precision improved by approximately 2000 N.