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Neural network-based adaptive consensus tracking control for multi-agent systems under actuator faults

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  • Lin Zhao
  • Yingmin Jia

Abstract

In this paper, a distributed output feedback consensus tracking control scheme is proposed for second-order multi-agent systems in the presence of uncertain nonlinear dynamics, external disturbances, input constraints, and partial loss of control effectiveness. The proposed controllers incorporate reduced-order filters to account for the unmeasured states, and the neural networks technique is implemented to approximate the uncertain nonlinear dynamics in the synthesis of control algorithms. In order to compensate the partial loss of actuator effectiveness faults, fault-tolerant parts are included in controllers. Using the Lyapunov approach and graph theory, it is proved that the controllers guarantee a group of agents that simultaneously track a common time-varying state of leader, even when the state of leader is available only to a subset of the members of a group. Simulation results are provided to demonstrate the effectiveness of the proposed consensus tracking method.

Suggested Citation

  • Lin Zhao & Yingmin Jia, 2016. "Neural network-based adaptive consensus tracking control for multi-agent systems under actuator faults," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(8), pages 1931-1942, June.
    • Handle: RePEc:taf:tsysxx:v:47:y:2016:i:8:p:1931-1942
    DOI: 10.1080/00207721.2014.960906
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    Cited by:

    1. Zhao, Lin & Jia, Yingmin & Yu, Jinpeng & Du, Junping, 2017. "H∞ sliding mode based scaled consensus control for linear multi-agent systems with disturbances," Applied Mathematics and Computation, Elsevier, vol. 292(C), pages 375-389.
    2. Mingwen Zheng & Lixiang Li & Haipeng Peng & Jinghua Xiao & Yixian Yang & Yanping Zhang & Hui Zhao, 2018. "Globally fixed-time synchronization of coupled neutral-type neural network with mixed time-varying delays," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-22, January.
    3. Thang Nguyen Trong & Minh Nguyen Duc, 2017. "Sliding Surface in Consensus Problem of Multi-Agent Rigid Manipulators with Neural Network Controller," Energies, MDPI, vol. 10(12), pages 1-15, December.
    4. Tan, Yushun & Fei, Shumin & Liu, Jinliang & Zhang, Dan, 2019. "Asynchronous adaptive event-triggered tracking control for multi-agent systems with stochastic actuator faults," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 482-496.
    5. Jing Bai & Yongguang Yu, 2018. "Neural Networks Based Adaptive Consensus for a Class of Fractional-Order Uncertain Nonlinear Multiagent Systems," Complexity, Hindawi, vol. 2018, pages 1-10, November.

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