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author:

Li, Junyu (Li, Junyu.) [1] | Zhang, Anguo (Zhang, Anguo.) [2] | Peng, Cheng (Peng, Cheng.) [3]

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EI

Abstract:

In this paper, we studied the cooperative control problem for a class of high-order nonlinear multi-agent systems (MASs) with external disturbance and system uncertainty. A neuro-adaptive robust controller with sliding mode variable structure method, with an online-learning RBF-like neural network was proposed to approximate the nonlinear terms. Further, sliding mode variable structure method was used to eliminate the influence of external disturbance and system uncertainty. Lyapunov stability theorem verified the capability of system consensus, and the sufficient conditions for cooperatively uniformly ultimately bounded (CUUB) are also given. At last, two numerical simulations on both homogeneous and heterogeneous MASs demonstrated the effectiveness of our proposed method. © The Author(s) 2022.

Keyword:

Adaptive control systems E-learning Learning systems Multi agent systems Numerical methods Online systems Sliding mode control

Community:

  • [ 1 ] [Li, Junyu]School of Electrical and Mechanical Engineering, Hefei Vocational and Technical College, Hefei, China
  • [ 2 ] [Zhang, Anguo]College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
  • [ 3 ] [Peng, Cheng]School of Electrical and Mechanical Engineering, Hefei Vocational and Technical College, Hefei, China

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Source :

Measurement and Control (United Kingdom)

ISSN: 0020-2940

Year: 2023

Issue: 5-6

Volume: 56

Page: 928-937

1 . 3

JCR@2023

1 . 3 0 0

JCR@2023

ESI HC Threshold:35

JCR Journal Grade:3

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 6

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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