Logan E. Beaver;Christopher Kroninger;Michael Dorothy;Andreas A. Malikopoulos
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引用次数: 0
Abstract
In this article, we present a constraint-driven control algorithm that minimizes the energy consumption of individual agents and yields an emergent V formation. As the formation emerges from the decentralized interaction between agents, our approach is robust to the spontaneous addition or removal of agents to the system. We start from an analytical model for the trailing upwash behind a fixed-wing uncrewed aerial vehicle (UAV), and we derive the optimal air speed for trailing UAVs to maximize their travel endurance. Next, we prove that simply flying at the optimal airspeed will never lead to emergent flocking behavior and propose a new decentralized “aneroid” behavior that yields emergent V formations. We encode these behaviors in a constraint-driven control algorithm that minimizes the locomotive power of each UAV. Finally, we prove that UAVs initialized in an approximate V or echelon formation will converge under our proposed control law, and we demonstrate that this emergence occurs in real time in simulation and in physical experiments with a fleet of Crazyflie quadrotors despite the noise and disturbances inherent in physical systems.
在这篇文章中,我们提出了一种约束驱动控制算法,它能最大限度地减少单个代理的能量消耗,并产生新出现的 V 编队。由于编队是由代理之间的分散互动产生的,因此我们的方法对系统中代理的自发添加或移除具有鲁棒性。我们从固定翼无人驾驶飞行器(UAV)尾随上冲的分析模型入手,推导出尾随 UAV 的最佳飞行速度,以最大限度地提高其飞行耐力。接下来,我们证明了简单地以最佳空速飞行永远不会导致出现成群结队的行为,并提出了一种新的分散式 "气动 "行为,从而产生了新的 V 形编队。我们将这些行为编码为一种约束驱动控制算法,该算法可使每个无人飞行器的机动力最小化。最后,我们证明了以近似 V 形或梯队队形初始化的无人机将在我们提出的控制法则下收敛,我们还证明了这种收敛会在模拟和使用 Crazyflie 四旋翼飞行器机队进行的物理实验中实时发生,尽管物理系统中存在固有的噪声和干扰。
期刊介绍:
The IEEE Transactions on Control of Network Systems is committed to the timely publication of high-impact papers at the intersection of control systems and network science. In particular, the journal addresses research on the analysis, design and implementation of networked control systems, as well as control over networks. Relevant work includes the full spectrum from basic research on control systems to the design of engineering solutions for automatic control of, and over, networks. The topics covered by this journal include: Coordinated control and estimation over networks, Control and computation over sensor networks, Control under communication constraints, Control and performance analysis issues that arise in the dynamics of networks used in application areas such as communications, computers, transportation, manufacturing, Web ranking and aggregation, social networks, biology, power systems, economics, Synchronization of activities across a controlled network, Stability analysis of controlled networks, Analysis of networks as hybrid dynamical systems.