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Open Access | Just Accepted

R-L Based Distributed Sliding Mode Control for the Isomorphic Complex Network

Guangchen Zhang1( )Zheng Zhou1Yuanqing Xia2Shuping He3

1 North Minzu University School of Mathematics and Information Sciences, Yinchuan, 750021, China

2 Beijing Institute of Technology of Automation, Beijing 100081, China

3 Anhui University of Electrical Engineering and Automation, Hefei, 230601, China

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Abstract

In this paper, we discuss the distributed optimal sliding mode control (SMC) issue for the isomorphic complex network in view of learning theory. Firstly, a dynamic distributed SMC strategy is introduced innovatively by virtue of reinforcement learning (R-L) theory, and on this basis, the overall tracking error closed-loop system is formulated between the complex network and the target system. For the overall error system, we provide the detail schemes for stability analysis and SMC control synthesis. The corresponding criteria and SMC algorithm are proposed via the solvable inequality constraints. Subsequently, the reachability issue is also analyzed for the pre-designed sliding mode surface. To conclude the paper, we check some unmanned aerial vehicles (UAVs) as the example under the complex network framework, and then, verify the effectiveness of the conclusions and algorithms for UAVs in this paper.

Tsinghua Science and Technology
Cite this article:
Zhang G, Zhou Z, Xia Y, et al. R-L Based Distributed Sliding Mode Control for the Isomorphic Complex Network. Tsinghua Science and Technology, 2025, https://doi.org/10.26599/TST.2024.9010258

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Received: 03 October 2024
Revised: 29 November 2024
Accepted: 12 December 2024
Available online: 20 January 2025

© The author(s) 2025.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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