未知关联度多变量系统的一阶d型迭代学习控制

Zhaoqing Song, J. Mao, Guorong Zhao
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引用次数: 0

摘要

d型迭代学习控制(ILC)规律是ILC的主要规律之一。d型ILC律取决于被控系统的相对程度。高阶ILC律难以实现,且会增强噪声的影响。针对相对度未知的多变量系统,提出了一阶d型ILC的设计方法。用一阶串联和并联子系统与未知向量相对度的多变量控制系统构造具有单位矢量相对度的虚拟系统。在一阶d型ILC作用下,虚拟系统可以完全跟踪期望轨迹,实际被控系统在一定误差范围内可以沿期望轨迹实现渐近跟踪。d型ILC律的增益不依赖于被控系统的参数。仿真实例验证了该方法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
First-order D-type iterative learning control for multivariable systems with unknown relative degree
D-type iterative learning control (ILC) law is one of the main laws of ILC. D-type ILC law depends on the relative degree of the controlled system. High order ILC law is difficult to realize, and will enhance the effect of the noise. A design method of first-order D-type ILC is presented for multivariable systems with unknown relative degree. A dummy system with unit vector relative degree can be constructed by series and parallel connected first-order subsystem with the multivariable controlled system with unknown vector relative degree. The dummy system can track the desired trajectory completely under the action of the first-order D-type ILC, and the actual controlled system can realize asymptotic tracking along the desired trajectory within a certain error scope. The gain of the D-type ILC law does not depend on the parameters of the controlled system. The simulation example demonstrates the feasibility and effectiveness of the presented method.
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