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多面体非线性离散时间系统的预测重复控制

Preview repetitive control for polytopic nonlinear discrete-time systems.

作者信息

Li Li, Jia Chen

机构信息

School of Information Management and Statistics, 56710Hubei University of Economics, Wuhan, 430205, China.

Hubei Center for Date and Analysis, 56710Hubei University of Economics, Wuhan, 430205, China.

出版信息

Sci Prog. 2022 Apr-Jun;105(2):368504221075472. doi: 10.1177/00368504221075472.

DOI:10.1177/00368504221075472
PMID:35542984
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10358556/
Abstract

In this study, a preview repetitive control (PRC) strategy was developed for uncertain nonlinear discrete-time systems subjected to a previewable periodic reference signal. The proposed preview repetitive controller was designed such that the system output tracked a previewable periodic reference signal even with model uncertainties and nonlinear terms. An augmented two-dimensional (2D) model was constructed based on the 2D model approach and state augmented technique. Second, considering the state unmeasured and periodic tracking reference signal, a static output PRC law was designed using the linear matrix inequality (LMI) techniques. Finally, the effectiveness of the proposed controller was verified through two illustrative examples.

摘要

在本研究中，针对受可预测周期性参考信号作用的不确定非线性离散时间系统，开发了一种预观重复控制（PRC）策略。所提出的预观重复控制器设计为，即使存在模型不确定性和非线性项，系统输出也能跟踪可预测的周期性参考信号。基于二维（2D）模型方法和状态扩充技术构建了增广二维模型。其次，考虑到状态不可测以及周期性跟踪参考信号，利用线性矩阵不等式（LMI）技术设计了一种静态输出PRC律。最后，通过两个示例验证了所提控制器的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/102f5284b21f/10.1177_00368504221075472-fig12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/5d23b979286f/10.1177_00368504221075472-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/afac0961b656/10.1177_00368504221075472-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/05ee84341ba8/10.1177_00368504221075472-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/a94c5381f095/10.1177_00368504221075472-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/29f997706036/10.1177_00368504221075472-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/10930908aa7b/10.1177_00368504221075472-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/d21f17e78f10/10.1177_00368504221075472-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/1ef830a9b550/10.1177_00368504221075472-fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/825b21b91797/10.1177_00368504221075472-fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/8bd0d607d606/10.1177_00368504221075472-fig10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/591d4cf36976/10.1177_00368504221075472-fig11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/102f5284b21f/10.1177_00368504221075472-fig12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/5d23b979286f/10.1177_00368504221075472-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/afac0961b656/10.1177_00368504221075472-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/05ee84341ba8/10.1177_00368504221075472-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/a94c5381f095/10.1177_00368504221075472-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/29f997706036/10.1177_00368504221075472-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/10930908aa7b/10.1177_00368504221075472-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/d21f17e78f10/10.1177_00368504221075472-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/1ef830a9b550/10.1177_00368504221075472-fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/825b21b91797/10.1177_00368504221075472-fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/8bd0d607d606/10.1177_00368504221075472-fig10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/591d4cf36976/10.1177_00368504221075472-fig11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/736a/10358556/102f5284b21f/10.1177_00368504221075472-fig12.jpg

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本文引用的文献

1
Cooperative preview tracking problem of discrete-time linear multi-agent systems: A distributed output regulation approach.离散时间线性多智能体系统的协同预测跟踪问题：一种分布式输出调节方法。
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