Distributed Gain Scheduling Dynamic Event-Triggered Semi-Global Leader-Following Consensus of Input Constrained MASs Under Fixed/Switching Topologies

Meilin Li; Tieshan Li; Hongjing Liang

doi:10.1109/JAS.2025.125417

IEEE/CAA Journal of Automatica Sinica

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M. Li, T. Li, and H. Liang, “Distributed gain scheduling dynamic event-triggered semi-global leader-following consensus of input constrained MASs under fixed/switching topologies,” IEEE/CAA J. Autom. Sinica, 2025. doi: 10.1109/JAS.2025.125417

Citation:

M. Li, T. Li, and H. Liang, “Distributed gain scheduling dynamic event-triggered semi-global leader-following consensus of input constrained MASs under fixed/switching topologies,” IEEE/CAA J. Autom. Sinica, 2025. doi: 10.1109/JAS.2025.125417

Citation:

M. Li, T. Li, and H. Liang, “Distributed gain scheduling dynamic event-triggered semi-global leader-following consensus of input constrained MASs under fixed/switching topologies,” IEEE/CAA J. Autom. Sinica, 2025. doi: 10.1109/JAS.2025.125417

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Distributed Gain Scheduling Dynamic Event-Triggered Semi-Global Leader-Following Consensus of Input Constrained MASs Under Fixed/Switching Topologies

doi: 10.1109/JAS.2025.125417

Funds: This work was supported in part by the National Natural Science Foundation of China (62322307, 51939001, 52471376), the Fundamental Research Funds for the Central Universities (ZYGX2024Z018), and the Sichuan Science and Technology Program (2023NSFSC1968)

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Author Bio:
Meilin Li (Graduate Student Member, IEEE) received the M.S. degree in traffic and transportation engineering in Dalian Maritime University in 2020. She is currently pursuing the Ph.D. degree at the School of Automation Engineering, University of Electronic Science and Technology of China. Her current research interests include event-triggered control, multi-agent systems control, input saturation control, and adaptive control

Tieshan Li (Senior Member, IEEE) received the B.S. degree in ocean fisheries engineering from the Ocean University of China in 1992, and the Ph.D. degree in vehicle operation engineering from Dalian Maritime University (DMU), in 2005. He was a Full Professor with DMU until 2020 and has been serving as a Chair Professor since 2021. He is currently a Tenured Professor with the University of Electronic Science and Technology of China. He is also with the Yangtze Delta Region Institute, University of Electronic Science and Technology of China, and also with the Laboratory of Electromagnetic Space Cognition and Intelligent Control. His research interests include intelligent learning and control for nonlinear systems, multiagent systems, and their applications to unmanned vehicles

Hongjing Liang (Member, IEEE) received the B.S. degree in mathematics from Bohai University in 2009, and the M.S. degree in fundamental mathematics and the Ph.D. degree in control theory and control engineering from Northeastern University, in 2011 and 2016, respectively. He was a Temporary Research Associate with the Science Program, Texas A&M University, Qatar. He is currently a Professor with the University of Electronic Science and Technology of China. His current research interests include adaptive control, fuzzy control, and cooperative control and their applications. Dr. Liang was a recipient of the Outstanding Reviewer Award of CAA/Automatica Sinica 2019. He has been in the Editorial Board of International Journal of Fuzzy Systems and Fluctuation and Noise Letters
Corresponding author: Tieshan Li, e-mail: lianghongjing@uestc.edu.cn
Received Date: 2025-01-03
Accepted Date: 2025-03-06

Available Online: 2025-04-18

Abstract

Abstract

In this paper, the semi-global leader-following consensus issue of multi-agent systems with constrained input under fixed and switching topologies is investigated via a distributed gain scheduling dynamic event-triggered method. First, a novel distributed gain scheduling consensus protocol is proposed under fixed topology, which integrates time-varying gain and distributed parameter schedulers. This approach enhances the transient performance of consensus tracking by enlarging the gain parameter through the scheduler, while the reliance of the scheduler on global state information is eliminated via a distributed design method. Subsequently, a distributed dynamic event-triggered mechanism is introduced to reduce the controller updates, while the expression of the inter-event times mitigates its explicit reliance on the system matrix. Additionally, to eliminate the need for real-time monitoring of neighboring agents’ states and continuous communication, a distributed dynamic self-triggered mechanism is developed. Next, our approaches are extended to solve the semi-global leader-following consensus problem under switching topologies. The average dwell time technique is employed to alleviate the limitations on the switching rate among multiple topologies. Finally, the theoretical analysis is validated through simulation results.
- Dynamic event-triggered/self triggered mechanism,
- fixed/switching topologies,
- gain scheduling control,
- input constraints,
- multi-agent systems

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References(46)

References

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Distributed Gain Scheduling Dynamic Event-Triggered Semi-Global Leader-Following Consensus of Input Constrained MASs Under Fixed/Switching Topologies

doi: 10.1109/JAS.2025.125417

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