用奇异值设定反馈ILC控制输出扰动限

Rashid Alzuabi, A. Alotaibi, Humoud A. Alqattan
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引用次数: 1

摘要

迭代学习控制是控制直接作用于重复系统的误差的有效方法。系统的稳定性是设计的主要目标。小增益定理应用于状态反馈ILC的设计过程中。反馈控制器与迭代学习控制在产生最小误差系统方面具有优势。参考输出端的扰动区域,研究了过去误差反馈和当前误差反馈迭代控制系统。本文主要对输出端的扰动区域进行比较。以往的误差前馈系统和当前的误差反馈系统都是在奇异值上发展起来的。因此,我们使用奇异值来设定过去误差和当前误差反馈ILC系统的输出扰动极限。因此,我们得到的结果,过去的误差前馈性能优于当前的误差反馈系统。这意味着对过去误差前馈的干扰抑制区域比另一个更大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Singular Value to Set Output Disturbance Limits to Feedback ILC Control
Iterative Learning Control is an effective way of controlling the errors which act directly on the repetitive system. The stability of the system is the main objective in designing. The Small Gain Theorem is used in the design process of State Feedback ILC. The feedback controller along with the Iterative Learning Control adds an advantage in producing a system with minimal error. The past error and current error feedback Iterative control system are studied with reference to the region of disturbance at the output. This paper mainly focuses on comparing the region of disturbance at the output end. The past error feed forward and current error feedback systems are developed on the singular values. Hence, we use the singular values to set an output disturbance limit for the past error and current error feedback ILC system. Thus, we obtain a result of past error feed forward performing better than the current error feedback system. This implies greater region of disturbance suppression to past error feed forward than the other.
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