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Applied Sciences
Volume 14
Issue 13
10.3390/app14135527
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Open AccessArticle
by Ye Ren SciProfiles Scilit Preprints.org Google Scholar Honghai Ji SciProfiles Scilit Preprints.org Google Scholar Deli Li SciProfiles Scilit Preprints.org Google Scholar Yongqiang Xie SciProfiles Scilit Preprints.org Google Scholar Shuangshuang Xiong SciProfiles Scilit Preprints.org Google Scholar Li Wang SciProfiles Scilit Preprints.org Google Scholar 
Ye Ren
, Honghai JiDeli LiYongqiang XieShuangshuang XiongLi Wang
1
School of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China
2
Division of Optical Communications, China Mobile Group Design Institute Co. Ltd., Beijing 100144, China
3
School of Automation, Being Information Science and Technology University, Beijing 100192, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(13), 5527; https://doi.org/10.3390/app14135527 (registeringDOI)
Submission received: 16 April 2024 / Revised: 14 June 2024 / Accepted: 20 June 2024 / Published: 25 June 2024
(This article belongs to the Topic Distributed Optimization for Control)
Abstract
This paper studies the containment control problem of heterogeneous multi-agent systems (MASs) with multiple leaders. The follower agent dynamics are assumed to be unknown and nonlinear. First, each follower is transformed into an incremental data description based on the dynamic linearization technique. Then, a distributed model-free adaptive containment control law is proposed such that all followers will be driven into the convex hull of the leaders. Furthermore, the algorithm is extended to the time-switching and dynamic leaders case. As a data-driven approach, the proposed controller design uses only the received input and output (I/O) data of these agents rather than agent mathematical models. Finally, to test the potential in real applications, three representative examples considering various environment factors, including external disturbances, are simulated to show the effectiveness and resilience of this method.
Keywords: data-driven control; model free adaptive control; multi-agent systems; containment control
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MDPI and ACS Style
Ren, Y.; Ji, H.; Li, D.; Xie, Y.; Xiong, S.; Wang, L. Data-Driven Containment Control for a Class of Nonlinear Multi-Agent Systems: A Model Free Adaptive Control Approach. Appl. Sci. 2024, 14, 5527. https://doi.org/10.3390/app14135527
AMA Style
Ren Y, Ji H, Li D, Xie Y, Xiong S, Wang L. Data-Driven Containment Control for a Class of Nonlinear Multi-Agent Systems: A Model Free Adaptive Control Approach. Applied Sciences. 2024; 14(13):5527. https://doi.org/10.3390/app14135527
Chicago/Turabian Style
Ren, Ye, Honghai Ji, Deli Li, Yongqiang Xie, Shuangshuang Xiong, and Li Wang. 2024. "Data-Driven Containment Control for a Class of Nonlinear Multi-Agent Systems: A Model Free Adaptive Control Approach" Applied Sciences 14, no. 13: 5527. https://doi.org/10.3390/app14135527
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
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MDPI and ACS Style
Ren, Y.; Ji, H.; Li, D.; Xie, Y.; Xiong, S.; Wang, L. Data-Driven Containment Control for a Class of Nonlinear Multi-Agent Systems: A Model Free Adaptive Control Approach. Appl. Sci. 2024, 14, 5527. https://doi.org/10.3390/app14135527
AMA Style
Ren Y, Ji H, Li D, Xie Y, Xiong S, Wang L. Data-Driven Containment Control for a Class of Nonlinear Multi-Agent Systems: A Model Free Adaptive Control Approach. Applied Sciences. 2024; 14(13):5527. https://doi.org/10.3390/app14135527
Chicago/Turabian Style
Ren, Ye, Honghai Ji, Deli Li, Yongqiang Xie, Shuangshuang Xiong, and Li Wang. 2024. "Data-Driven Containment Control for a Class of Nonlinear Multi-Agent Systems: A Model Free Adaptive Control Approach" Applied Sciences 14, no. 13: 5527. https://doi.org/10.3390/app14135527
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
Appl. Sci., EISSN 2076-3417, Published by MDPI
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