文章基本信息

标题：Iterative Learning Control Strategy for a Furuta Pendulum System with Variable-Order Linearization
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作者：Ricardo Binz ; Stanislav Aranovskiy
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：20
页码：14-19
DOI：10.1016/j.ifacol.2021.11.146
语种：English
出版社：Elsevier
摘要：AbstractWe consider Iterative Learning Control for the Furuta Pendulum nonlinear mechanical system, where the goal is to learn the input torque such that the pendulum angle follows a reference. We show that the linearization of the considered system is of variable trajectory-dependent order and thus some existing solutions do not apply. We propose a novel method based on the observability matrix inversion allowing to deal with the variable-order minimum realization. The applicability of the proposed method is illustrated with simulations.
关键词：KeywordsIterative learning controlFuruta Pendulummechatronic systemsobservability