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A new approach to feedback feed-forward iterative learning control with random packet dropouts

机译:一种新的反馈前向前迭代学习控制与随机数据包丢弃的方法

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This paper is devoted to the feedback feed-forward iterative learning control (FFILC) with random packet dropouts. Resorting to a 2D Roesser system manner, the resultant FFILC falls in the robust framework. With the help of Lyapunov method and stochastic analysis technique, a new condition is developed to guarantee the desired mean-square stability with the prescribed H os performance. To co-design controller and learning parameters by means of linear matrix inequalities, an effective strategy is employed to overcome the coupling nonlinearities induced by these parameters and Lypunov variable. An injection modeling process is adopted to show the effectiveness of the proposed method. (C) 2018 Elsevier Inc. All rights reserved.
机译:本文与随机数据包丢弃的反馈前馈迭代学习控制(FFILC)致力于反馈前馈迭代学习控制。 借助2D roesser系统方式,所得FFILC落入强大的框架。 借助Lyapunov方法和随机分析技术,开发了一种新的条件,以保证所需的平均方形稳定性,具有规定的H OS性能。 通过线性矩阵不等式协同设计控制器和学习参数,采用有效的策略来克服这些参数和Lypunov变量引起的耦合非线性。 采用注射建模过程来展示所提出的方法的有效性。 (c)2018年Elsevier Inc.保留所有权利。

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