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Sliding Surface in Consensus Problem of Multi-Agent Rigid Manipulators with Neural Network Controller

Author

Listed:
  • Thang Nguyen Trong

    (Department of Electrical Engineering and Automation, Haiphong Private University, Haiphong 181810, Vietnam)

  • Minh Nguyen Duc

    (Department of Electrical Engineering and Automation, Haiphong Private University, Haiphong 181810, Vietnam)

Abstract

Based on Lyapunov theory, this research demonstrates the stability of the sliding surface in the consensus problem of multi-agent systems. Each agent in this system is represented by the dynamically uncertain robot, unstructured disturbances, and nonlinear friction, especially when the dynamic function of agent is unknown. All system states use neural network online weight tuning algorithms to compensate for the disturbance and uncertainty. Each agent in the system has a different position, and their trajectory approach to the same target is from each distinct orientation. In this research, we analyze the design of the sliding surface for this model and demonstrate which type of sliding surface is the best for the consensus problem. Lastly, simulation results are presented to certify the correctness and the effectiveness of the proposed control method.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:12:p:2127-:d:122917
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    References listed on IDEAS

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    1. Manuel Schimmack & Eduardo E. Feistauer & Sergio T. Amancio-Filho & Paolo Mercorelli, 2017. "Hysteresis Analysis and Control of a Metal-Polymer Hybrid Soft Actuator," Energies, MDPI, vol. 10(4), pages 1-20, April.
    2. 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.
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    Cited by:

    1. Yilun Shang, 2018. "Resilient Multiscale Coordination Control against Adversarial Nodes," Energies, MDPI, vol. 11(7), pages 1-17, July.

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