Monotonic Switching Iterative Learning Control Method for a Class of Discrete Time Switched System

H. Ouerfelli, S. B. Attia, S. Salhi
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引用次数: 1

Abstract

T his paper deal with the problem of monotonic tracking convergence error (MC) of discrete time switched system. We begin our review by proposing the considered switched systems are operated during a finite time interval repetitively, and then the iterative learning control (ILC) scheme can be introduced between subsystems. Namely, the tracking error converges with non-zero constant initial error. After the switched system is transformed into a 2D switched system, sufficient conditions in terms of linear matrix inequalities (LMIs) are derived by using the -norm. It is shown that the tracking error converges monotonically to zero in the sense of -norm. A numerical simulation example is established shown the effectiveness of the proposed method.
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一类离散时间切换系统的单调切换迭代学习控制方法
本文研究了离散时间切换系统的单调跟踪收敛误差问题。我们首先提出,所考虑的切换系统在有限时间间隔内重复运行,然后可以在子系统之间引入迭代学习控制(ILC)方案。也就是说,跟踪误差收敛于非零常数的初始误差。将切换系统转化为二维切换系统后,利用-范数得到了线性矩阵不等式的充分条件。结果表明,跟踪误差在范数意义下单调收敛到零。通过算例验证了该方法的有效性。
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来源期刊
International Journal of Automation and Smart Technology
International Journal of Automation and Smart Technology Engineering-Electrical and Electronic Engineering
CiteScore
0.70
自引率
0.00%
发文量
0
审稿时长
16 weeks
期刊介绍: International Journal of Automation and Smart Technology (AUSMT) is a peer-reviewed, open-access journal devoted to publishing research papers in the fields of automation and smart technology. Currently, the journal is abstracted in Scopus, INSPEC and DOAJ (Directory of Open Access Journals). The research areas of the journal include but are not limited to the fields of mechatronics, automation, ambient Intelligence, sensor networks, human-computer interfaces, and robotics. These technologies should be developed with the major purpose to increase the quality of life as well as to work towards environmental, economic and social sustainability for future generations. AUSMT endeavors to provide a worldwide forum for the dynamic exchange of ideas and findings from research of different disciplines from around the world. Also, AUSMT actively seeks to encourage interaction and cooperation between academia and industry along the fields of automation and smart technology. For the aforementioned purposes, AUSMT maps out 5 areas of interests. Each of them represents a pillar for better future life: - Intelligent Automation Technology. - Ambient Intelligence, Context Awareness, and Sensor Networks. - Human-Computer Interface. - Optomechatronic Modules and Systems. - Robotics, Intelligent Devices and Systems.
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