A RILC method for uncertain system based on LMI technique

Kouki Olfa, M. Chaouki, Toujeni Nizar, G. Moncef
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Abstract

We study, in this work, the robust iterative learning control RILC design for uncertain systems. The control law design is based on H∞ concept and tow dimensional 2D theory. A Proportional type, Derivative type and Proportional Derivative type RILC laws will be proposed to achieve the desired performance of repetitive systems. A comparison between the three proposed control laws will be presented. The monotonic convergence and the robust stability will be demonstrated by using this control laws. Based on H∞ concept, sufficient settings for asymptotic convergence of our approaches are presented in terms of LMI (linear matrix inequality). An academic example is presented here to prove the efficiency of the proposed schemes.
基于LMI技术的不确定系统的RILC方法
本文研究了不确定系统的鲁棒迭代学习控制RILC设计。控制律设计基于H∞概念和二维二维理论。将提出比例型、导数型和比例导数型RILC定律,以实现重复系统的期望性能。本文将对这三种控制律进行比较。利用该控制律证明了该控制律的单调收敛性和鲁棒稳定性。基于H∞概念,利用线性矩阵不等式给出了方法渐近收敛的充分条件。最后给出了一个理论算例,证明了所提方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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