事件触发机制下的ASV仿射编队机动控制

Affine transformation maneuver control for multiple autonomous surface vehicles under event-triggered inter-vehicle communication

  • 摘要:
    目的 针对通信资源受限的水面自主航行器(ASV)编队问题,提出基于事件触发的ASV分布式仿编队控制算法。
    方法 首先,根据仿射变换理论,为ASV设计一种更简便的编队操纵方式,使编队内的智能体可以完成缩放、平移、旋转和剪切等整体编队动作,以及这些动作变换之间的相互组合;然后,提出一种新的事件触发机制,让ASV仅在满足触发条件的时刻才与相邻个体进行通信,以节省通信和计算资源,并避免Zeno行为。
    结果 通过稳定性分析,证明了闭环误差的收敛性及系统的最终有界稳定性;通过仿真分析,证明编队能够完成多样化的几何变换,事件触发机制降低通信频次并节省了78%的通信资源。
    结论 该算法通过仿射变换可提高编队的灵活性,并通过降低通信频次节约能量消耗,研究成果可为ASV编队的优化设计提供参考。

     

    Abstract:
    Objective This study aims to develop a formation maneuver control mechanism for multiple autonomous surface vehicles (ASVs) operating under external and parameter uncertainties. Additionally, considering the limited resources available on ASVs, it is preferred to design a resource-efficient formation control algorithm.
    Method First, affine transformation is integrated into our control scheme, enabling the ASVs to achieve rotation, scaling, translation and shearing motions, both individually and in combination. This approach allows for flexible and distributed formation maneuvering. Second, to address the limitation of communication resources, an event-triggered mechanism is proposed and incorporated into our algorithm. By evaluating the triggering condition, vehicles communicate with their neighbors only when necessary, i.e., when the predefined triggering condition is met. This process effectively reduces the frequency of inter-vehicle communication, leading to more efficient utilization of resources, and avoids Zeno behavior.
    Results Stability analysis demonstrates the convergence of all closed-loop error signals to a compact set, ensuring the ultimate boundedness of the closed-loop system. Simulation results confirm that the proposed algorithm enables the formation to achieve various geometric transformations, while the event-triggered mechanism reduces the communication frequency, resulting in a 78% saving in communication resources.
    Conclusion The proposed algorithm enhances the flexibility of ASV formations by incorporating affine transformations and reduces energy consumption through lower communication frequency. These findings provide reference for optimizing ASV formation design.

     

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