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Applying a Generalized Predictive Control Theory to a Carding Autoleveler

机译:广义预测控制理论在梳理自动调平机上的应用

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Usually, a carding process is difficult to control with classic control algorithms (such as PID) for three main reasons: strong stochastic disturbance, time delays, and parameter variation. In this paper, generalized predictive control (GPC) is introduced to control such a process. First, a CARIMA model is built to describe the carding process, then the GPC control law is derived and used to design the controller for a carding autoleveler. The simulation results show that the GPC controller can greatly reduce a sliver's standard deviation and can reject measured and unmeasured step disturbance. Although this paper mainly involves the design of a feedforward-feedback GPC controller for a carding autoleveler, the methods of modeling and GPC controller design can easily be extended to a feedback case and used to design controllers for other preparatory machines' autolevelers.
机译:通常,由于以下三个主要原因,很难使用经典的控制算法(例如PID)来控制梳理过程:强烈的随机干扰,时间延迟和参数变化。在本文中,引入了广义预测控制(GPC)来控制这种过程。首先,建立一个CARIMA模型来描述梳理过程,然后推导GPC控制律,并将其用于设计梳理自动调平器的控制器。仿真结果表明,GPC控制器可以大大降低条子的标准偏差,并且可以抑制测量和未测量的步进干扰。尽管本文主要涉及梳棉自动调平器的前馈-反馈GPC控制器的设计,但是建模和GPC控制器设计的方法可以轻松扩展到反馈情况,并可以用于设计其他准备机器的自动调平器的控制器。

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