报告题目：Trackability Problems for Iterative Learning Control Systems

报告时间：2024-11-16  14:30-15:30

报 告 人：孟德元  教授（北京航空航天大学）

报告地点：理学院东北楼四楼报告厅（404）

Abstract:In this talk, we focus on some fundamental problems of ILC, based on which some feedback-based ILC design and analysis methods are proposed to generalize the applicability of ILC methods. First, the trackability property is explored for ILC to reveal the implementabilityof the perfect tracking task. With the equivalence between trackability and controllability, the state feedback design idea is incorporated to develop an ILC updating law for the perfect tracking. Then, by connecting the perfect tracking problem to the state observation problem, the obseverdesign idea is further leveraged to explore an ILC updating law, under which not only the perfect tracking task is achieved, but also the learnability property of ILC systems is directly disclosed. These two feedback-based ILC updating laws are applicable for any linear ILC system, for which the finite-iteration convergence can be ensured under some specific design conditions. In particular, the feedback-based ILC methods are applied to develop some iterative solution methods for linear algebraic equations, which provides a possible way to build the bidirectional relations between control and mathematics.