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Design of Robust Control Algorithms for Predefined-Time of Multi-agent Systems with Distributed Sliding Mode Surfaces
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  • Qingfeng Xia,
  • Keer Xu,
  • Kai Hu,
  • Ning Sun,
  • Ruitian Yang,
  • Mingyang Li
Qingfeng Xia
Wuxi University
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Keer Xu
Nanjing University of Information Science and Technology
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Kai Hu
Nanjing University of Information Science and Technology
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Ning Sun
Wuxi University
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Ruitian Yang
Wuxi University

Corresponding Author:yangruitian@cwxu.edu.cn

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Mingyang Li
Nanjing University of Information Science and Technology
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Abstract

In this paper, we provide an in-depth discussion of the problem of predefined-time formation control for Multi-Agent Systems (MAS) and consider the presence of non-periodic Denial of Service (DoS) attacks. The suggested approach utilizes the system state to achieve time-varying formation of MAS within predefined-time. It effectively mitigates external disturbance or non-periodic DoS attacks. The algorithm combines the predefined-time Lyapunov stability theory with the Terminal Sliding Mode Control (TSMC) is the strategy of predefined-time sliding mode control. It creates a new distributed sliding mode surface to ensure the speed and stability of multi-agent formation under dynamic change and uncertainty conditions. The range of the system convergence time is specifically linked to the changeable parameters, which simplifies the design of the control algorithm to satisfy the appropriate requirements for convergence time. This study demonstrates the stability of the method through theoretical analysis and validates its effectiveness by conducting simulations on the Matlab experimental platform. The simulation results demonstrate that the anticipated limit of the time required for the algorithm to achieve a stable formation is less cautious and more resilient compared to the current TSMC algorithm.
23 Sep 2024Submitted to International Journal of Robust and Nonlinear Control
24 Sep 2024Submission Checks Completed
24 Sep 2024Assigned to Editor
24 Sep 2024Review(s) Completed, Editorial Evaluation Pending
22 Nov 2024Reviewer(s) Assigned