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A function space approach to sampled data control systems and tracking problems

机译:抽样数据控制系统和跟踪问题的功能空间方法

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摘要

This paper presents a new framework for hybrid sampled data control systems. Instead of considering the state only at sampling instants, this paper introduces a function piece during the sampling period as the state and gives an infinite-dimensional model with such a state space. This gives the advantage that sampled data systems with built-in intersample behavior can be regarded as linear, time-invariant, discrete-time systems. As a result, the approach makes it possible to introduce such time-invariant concepts as transfer functions, poles, and zeros to the sampled data systems even with the presence of the intersample behavior. In particular, tracking problems can be studied in this setting in a simple and unified way, and ripples are completely characterized as a mismatch between the intersample reference signal and transmission zero directions. This leads to the internal model principle for sampled data systems.
机译:本文提出了一种用于混合采样数据控制系统的新框架。本文不只是在采样时刻考虑状态,而是在采样期间引入一个功能块作为状态,并给出具有这种状态空间的无穷维模型。这具有以下优点:具有内置采样间行为的采样数据系统可以视为线性,时不变,离散时间系统。结果,即使存在采样间行为,该方法也可以将诸如传递函数,极点和零的时不变概念引入采样数据系统。尤其是,可以在这种情况下以简单统一的方式研究跟踪问题,并且波动完全表征为样本间参考信号与传输零方向之间的不匹配。这导致了采样数据系统的内部模型原理。

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