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

机译:基于指挥滤波器的速度和张力系统的速度和张力系统使用干扰观察员

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摘要

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.
机译:本文调查了可逆冷轧轧机速度和张力系统的解耦和协调跟踪控制问题。使用对角矩阵解耦网络和神经网络干扰观察者,我们提出了一种基于命令的基于滤波器的反向控制策略。首先,构造对角线矩阵去耦网络以削弱轧机系统的速度和张力之间的耦合,从而有效地降低了系统模型的复杂性。其次,通过将BackStepping与命令过滤器组合来设计,该控制器可以解决反向插入过程中的“复杂性爆炸”问题,并优化系统的控制结构。接下来,开发了神经网络障碍观察者以观察系统的不确定项目,从而有效地提高了系统的跟踪控制精度。理论分析表明,闭环系统中的所有信号都是均匀的最终界限。最后,在1422mm可逆的冷轧带钢轧机的速度和张力系统进行了仿真研究;结果表明,使用所提出的控制策略将系统的动态响应速度提高了大约1S,并且稳定性精度提高了大约2000 N.

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