Distributed Control for Flocking Maneuvers via Acceleration-Weighted Neighborhooding
Distributed Control for Flocking Maneuvers via Acceleration-Weighted Neighborhooding
复制标题
DOI：
10.23919/acc50511.2021.9483155
复制
发表时间：
2021-05
期刊：
影响因子：
--
通讯作者：
Shouvik Roy;Usama Mehmood;R. Grosu;S. Smolka;S. Stoller;A. Tiwari
中科院分区：
文献类型：
--
作者：
Shouvik Roy;Usama Mehmood;R. Grosu;S. Smolka;S. Stoller;A. Tiwari
本文引入了加速加权邻域分布式模型预测控制(DMPC)的概念，设计了一种分布式对称的高速群机动(一般为转弯)控制器。加速加权邻域搜索利用转弯动作中代理加速的不平衡来确保主动转弯代理被优先考虑。我们表明，使用我们的方法，可以在不将其作为全局目标的情况下实现群集机动。只有一小部分智能体，称为启动器，需要知道机动目标。我们的AWN-DMPC控制器确保这种局部信息以一种具有线性延迟的无标度方式在整个集群中传播。我们的实验评估最终证明了基于AWN-DMPC的分布式群集控制器的机动能力。
We introduce the concept of Distributed Model Predictive Control (DMPC) with Acceleration-Weighted Neighborhooding (AWN) in order to synthesize a distributed and symmetric controller for high-speed flocking maneuvers (angu-lar turns in general). Acceleration-Weighted Neighborhooding exploits the imbalance in agent accelerations during a turning maneuver to ensure that actively turning agents are prioritized. We show that with our approach, a flocking maneuver can be achieved without it being a global objective. Only a small subset of the agents, called initiators, need to be aware of the maneuver objective. Our AWN-DMPC controller ensures this local information is propagated throughout the flock in a scale-free manner with linear delays. Our experimental evaluation conclusively demonstrates the maneuvering capabilities of a distributed flocking controller based on AWN-DMPC.