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Event-triggered approximately optimized formation control of multi-agent systems with unknown disturbances via simplified reinforcement learning

Author

Listed:
  • Yang, Yang
  • Geng, Shuocong
  • Yue, Dong
  • Gorbachev, Sergey
  • Korovin, Iakov

Abstract

An event-triggered formation control strategy is proposed for a multi-agent system (MAS) suffered from unknown disturbances. In identifier-critic-actor neural networks (NNs), the strategy only needs to calculate the negative gradient of an approximated Hamilton-Jacobi-Bellman (HJB) equation, instead of the gradient descent method associated with Bellman residual errors. This simplified method removes the requirement for a complicated gradient calculation process of residual square of HJB equation. The weights in critic-actor NNs only update as the triggered condition is violated, and the computational burdens caused by frequent updates are thus reduced. Without dynamics information in prior, a disturbance observer is also constructed to approximate disturbances in an MAS. From stability analysis, it is proven that all signals are bounded. Two numerical examples are illustrated to verify that the proposed control strategy is effective.

Suggested Citation

  • Yang, Yang & Geng, Shuocong & Yue, Dong & Gorbachev, Sergey & Korovin, Iakov, 2025. "Event-triggered approximately optimized formation control of multi-agent systems with unknown disturbances via simplified reinforcement learning," Applied Mathematics and Computation, Elsevier, vol. 489(C).
    • Handle: RePEc:eee:apmaco:v:489:y:2025:i:c:s0096300324006106
    DOI: 10.1016/j.amc.2024.129149
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    References listed on IDEAS

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    1. Kou, Peng & Liang, Deliang & Wang, Chen & Wu, Zihao & Gao, Lin, 2020. "Safe deep reinforcement learning-based constrained optimal control scheme for active distribution networks," Applied Energy, Elsevier, vol. 264(C).
    2. Hao Sheng & Xia Liu, 2020. "Composite Compensation Control of Robotic System Subject to External Disturbance and Various Actuator Faults," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-11, July.
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