4.7 Article

Robust finite-time consensus control for Euler-Lagrange multi-agent systems subject to switching topologies and uncertainties

期刊

APPLIED MATHEMATICS AND COMPUTATION
卷 432, 期 -, 页码 -

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2022.127367

关键词

Euler-Lagrange systems; Finite -time consensus; Switching topology; Integral sliding mode control; Distributed control

资金

  1. Natural Science Foundation of Hebei Province [F2020202103]
  2. Scientific Research Program for Young Outstanding Talent of Higher Education of Heibei Province [BJ2021045]

向作者/读者索取更多资源

This paper studies the problem of robust finite-time consensus for Euler-Lagrange multi-agent systems subject to switching topologies and uncertainties. An integral sliding mode control scheme is proposed to achieve good disturbance rejection and finite-time consensus.
Euler-Lagrange (EL) system is a typical nonlinear system widely used to model robot sys-tems. Although consensus of EL multi-agent systems has been extensively studied in recent years, how to achieve better consensus performance under constraints such as switching topologies and uncertainties is still an open issue. Aiming at fast convergence and effec-tive disturbance rejection, this paper studies the integral sliding mode control problem for robust finite-time consensus of EL multi-agent systems subject to switching topologies and uncertainties. A basic integral sliding mode control (SMC) scheme is first presented for finite-time consensus of EL multi-agent systems subject to undirected topologies and uncertainties. It is shown that the proposed consensus protocol reaches good disturbance rejection and achieves robust finite-time consensus while avoiding the singularity problem in the existing studies. The proposed integral sliding mode control scheme is further ex-tended to finite-time consensus of EL multi-agent systems subject to directed and switch-ing topologies. Compared with the existing algorithms, faster finite-time convergence is achieved. In the simulation studies, the obtained results demonstrate the effectiveness and efficiency of the proposed algorithm.(c) 2022 Elsevier Inc. All rights reserved.

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