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Iterative Learning Control for Multiphase Batch Processes With Asynchronous Switching

机译:具有异步切换的多相批处理迭代学习控制

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摘要

Asynchronous switching between the controller and the active subsystems in multiphase batch processes may cause the systems to be unstable around the switching instants. In view of this, an average dwell-time method-based iterative learning control (ILC) scheme is proposed in this paper. First, the multiphase process is represented as an equivalent closed-loop two-dimensional (2-D) switched system composed of stable and unstable subsystems, based on which new relevant concepts on the stability of the switched system are given. Second, using an average dwell-time method, the ILC law is designed to guarantee the system exponentially stable. Minimum running time for the stable subsystems and maximum running time for the unstable ones are obtained. Lastly, depending on the maximum time for the unstable subsystems, the idea of putting the controller switching step forward is proposed. In this way, the asynchronous switching is removed such that the unstable subsystem can be avoided. The case study on an injection molding process demonstrates the effectiveness and superiority of the proposed method in comparison with the existing 2D-MPC and one-dimensional traditional control methods.
机译:控制器和多相批处理中的活动子系统之间的异步切换可能导致系统在切换时刻不稳定。鉴于此,本文提出了平均停留时间方法的迭代学习控制(ILC)方案。首先,多相过程表示为由稳定和不稳定的子系统组成的等效闭环二维(2-D)交换系统,基于给出了开关系统的稳定性的新相关概念。其次,使用平均停留时间方法,ILC法旨在保证系统指数稳定。获得稳定子系统的最小运行时间和不稳定的子系统的最大运行时间。最后,取决于不稳定子系统的最长时间,提出了将控制器切换步进前进的想法。以这种方式,消除异步切换,使得可以避免不稳定的子系统。与现有的2D-MPC和一维传统控制方法相比,对注射成型工艺的案例研究表明了所提出的方法的有效性和优越性。

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