Coordinated Standoff Tracking of Moving Targets: Control Laws and Information Architectures
Coordinated Standoff Tracking of Moving Targets: Control Laws and Information Architectures
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DOI：
10.2514/1.37212
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发表时间：
2008-08
影响因子：
2.6
通讯作者：
T. Summers;M. Akella;M. Mears
中科院分区：
文献类型：
--
作者：
T. Summers;M. Akella;M. Mears
在本文中，我们提出了工作的自主车辆编队控制的背景下，协调stando跟踪问题。其目的是使用一组无人驾驶飞机，只使用当地信息，以规定的飞行器间角间距围绕移动目标飞行圆形轨道。我们使用最近推出的李雅普诺夫指导向量场的方法来实现所需的圆形轨迹。本文的贡献涉及单车辆路径规划和多车辆协调。对于单个车辆路径规划，我们完成了一个证明的航向收敛使用反馈，迄今为止还没有完全解决的文献中，也oer航向收敛的一种新方法，不需要连续反馈的理想情况下（无风，静止目标），利用一个解析解的指导领域。此外，我们使用可变空速控制器来保持圆形轨迹，尽管未知的风和未知的恒速目标运动。自适应估计未知的风和目标运动，以确保稳定的圆形轨迹。我们的研究结果的一个新的特点是严格满足车辆特定的运动约束的航向速率和空速变化。对于多飞行器协调，我们再次使用可变空速控制器来实现规定的角间距。在一个统一的框架控制自主车辆编队的eort，我们最近的一些工作，解决信息架构的车辆编队使用图论的连接。具体来说，我们利用两种类型的信息架构，对称和不对称，并实现分散控制法。信息架构是可扩展的，在这个意义上，所需的通信/传感链路的数量与车辆的数量线性增加。控制律是分散的，因为它们只使用局部信息。
In this paper, we present work on control of autonomous vehicle formations in the context of the coordinated stando tracking problem . The objective is to use a team of unmanned aircraft to fly a circular orbit around a moving target with prescribed inter-vehicle angular spacing using only local information. We use the recently introduced Lyapunov guidance vector field approach to achieve the desired circular trajectory. The contributions of this paper involve both single vehicle path planning and multiple vehicle coordination. For single vehicle path planning, we complete a proof of heading convergence using feedback, which has thus far not been fully addressed in the literature, and also oer a novel approach for heading convergence that does not require continuous feedback in the ideal case (no wind, stationary target), taking advantage of an analytical solution to the guidance field. Further, we use a variable airspeed controller to maintain the circular trajectory despite unknown wind and unknown constant velocity target motion. Adaptive estimates of the unknown wind and target motion are introduced to ensure stability to the circular trajectory. A novel feature of our results is rigorous satisfaction of vehicle specific kinematic constraints on heading rates and airspeed variations. For multiple vehicle coordination, we again use a variable airspeed controller to achieve the prescribed angular spacing. In an eort towards a unified framework for control of autonomous vehicle formations, we make a connection with some recent work that addresses information architecture in vehicle formations using graph theory. Specifically, we utilize two types of information architectures, symmetric and asymmetric, and implement decentralized control laws. The information architectures are scalable in the sense that the number of required communication/sensing links increases linearly with the number of vehicles. The control laws are decentralized in the sense that they use only local information.