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Formation Control with Connectivity Assurance for Missile Swarms by a Natural Co-Evolutionary Strategy

Author

Listed:
  • Junda Chen

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

  • Xuejing Lan

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

  • Ye Zhou

    (School of Aerospace Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal 14300, Malaysia)

  • Jiaqiao Liang

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

Abstract

Formation control is one of the most concerning topics within the realm of swarm intelligence. This paper presents a metaheuristic approach that leverages a natural co-evolutionary strategy to solve the formation control problem for a swarm of missiles. The missile swarm is modeled by a second-order system with a heterogeneous reference target, and the exponential of the resultant error is accumulated to be the objective function such that the swarm converges to optimal equilibrium states satisfying specific formation requirements. Focusing on the issue of the local optimum and unstable evolution, we incorporate a novel model-based policy constraint and a population adaptation strategy that significantly alleviates the performance degradation of the existing natural co-evolutionary strategy in terms of slow training and instability of convergence. With application of the Molloy–Reed criterion in the field of network communication, we developed an adaptive topology method that assures connectivity under node failure, and its effectiveness is validated theoretically and experimentally. The experimental results demonstrate that the accuracy of formation flight achieved by this method is competitive with that of conventional control methods and is much more adaptable. More significantly, we show that it is feasible to treat the generic formation control problem as an optimal control problem for finding a Nash equilibrium strategy and solving it through iterative learning.

Suggested Citation

  • Junda Chen & Xuejing Lan & Ye Zhou & Jiaqiao Liang, 2022. "Formation Control with Connectivity Assurance for Missile Swarms by a Natural Co-Evolutionary Strategy," Mathematics, MDPI, vol. 10(22), pages 1-24, November.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:22:p:4244-:d:971392
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    References listed on IDEAS

    as
    1. Xuejing Lan & Zhenghao Wu & Wenbiao Xu & Guiyun Liu, 2018. "Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots," Complexity, Hindawi, vol. 2018, pages 1-8, December.
    2. Mason, Karl & Duggan, Jim & Howley, Enda, 2018. "Forecasting energy demand, wind generation and carbon dioxide emissions in Ireland using evolutionary neural networks," Energy, Elsevier, vol. 155(C), pages 705-720.
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    Cited by:

    1. Abbasali Koochakzadeh & Mojtaba Naderi Soorki & Aydin Azizi & Kamran Mohammadsharifi & Mohammadreza Riazat, 2023. "Delay-Dependent Stability Region for the Distributed Coordination of Delayed Fractional-Order Multi-Agent Systems," Mathematics, MDPI, vol. 11(5), pages 1-13, March.

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