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Adaptive Fuzzy Tracking Control of Uncertain Nonlinear Multi-Agent Systems with Unknown Control Directions and a Dead-Zone Fault

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  • Xiongfeng Deng

    (Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment, Ministry of Education, Anhui Polytechnic University, Wuhu 241000, China
    Key Laboratory of Electric Drive and Control of Anhui Higher Education Institutes, Anhui Polytechnic University, Wuhu 241000, China)

  • Xiyu Zhang

    (School of Mathematics and Computer Science, Guangxi Normal University of Science & Technology, Laibin 546199, China)

Abstract

In this paper, a class of uncertain nonlinear multi-agent systems with unknown control directions and a dead-zone fault is addressed, where unknown control gains exist in each subsystem. In terms of the approximation characteristic of a fuzzy logic system, it is used to approximate uncertain nonlinear dynamics, and then the relevant adaptive control laws are designed. Considering the presence of unknown control directions and a dead-zone fault, the Nussbaum gain function technique is introduced to design the intermediate control law and the adaptive fuzzy control law. A theoretical analysis shows that the tracking control problem of the given multi-agent systems can be effectively solved through the application of the proposed adaptive fuzzy control law and the tracking errors can converge to a small neighborhood of zero through an adjustment of the relevant parameters. Finally, the effectiveness of the theoretical analysis results is verified by two simulation cases.

Suggested Citation

  • Xiongfeng Deng & Xiyu Zhang, 2022. "Adaptive Fuzzy Tracking Control of Uncertain Nonlinear Multi-Agent Systems with Unknown Control Directions and a Dead-Zone Fault," Mathematics, MDPI, vol. 10(15), pages 1-19, July.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:15:p:2655-:d:874428
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    References listed on IDEAS

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    1. Wu, Ziwen & Zhang, Tianping & Xia, Xiaonan & Hua, Yu, 2022. "Finite-time adaptive neural command filtered control for non-strict feedback uncertain multi-agent systems including prescribed performance and input nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 421(C).
    2. Xiongfeng Deng & Xiuxia Sun & Ri Liu & Shuguang Liu, 2018. "Consensus control of leader-following nonlinear multi-agent systems with distributed adaptive iterative learning control," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(16), pages 3247-3260, December.
    3. Coelho, Vitor N. & Weiss Cohen, Miri & Coelho, Igor M. & Liu, Nian & Guimarães, Frederico Gadelha, 2017. "Multi-agent systems applied for energy systems integration: State-of-the-art applications and trends in microgrids," Applied Energy, Elsevier, vol. 187(C), pages 820-832.
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    Cited by:

    1. Xiongfeng Deng & Yiqing Huang & Lisheng Wei, 2022. "Adaptive Fuzzy Command Filtered Finite-Time Tracking Control for Uncertain Nonlinear Multi-Agent Systems with Unknown Input Saturation and Unknown Control Directions," Mathematics, MDPI, vol. 10(24), pages 1-22, December.

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