多艘气垫船在无中央控制下实现毫秒级协同轨迹控制。
Cooperative distributed model predictive control for embedded systems: Experiments with hovercraft formations
- 基于交替方向乘子法实现分布式实时迭代，无需中心协调器。
- 实验验证了毫秒级采样下点对点、避障、动态障碍物等复杂场景。
- 适合资源受限的嵌入式系统，可直接部署于单个气垫船上。
本文展示了在空气曲棍球桌上的气垫船编队中，应用于嵌入式系统的协作式分布式模型预测控制实验。每步采样中，各气垫船通过稳定化的去中心化实时迭代算法，利用交替方向乘子法共同求解一个集中式最优控制问题。该高效实现无需中央协调器，可在气垫船本地运行，支持毫秒级采样周期。编队控制实验验证了该方法在点对点转移、轨迹跟踪、碰撞避免及移动障碍物等场景下的灵活性。
原文摘要 · Abstract (English)
This paper presents experiments for embedded cooperative distributed model predictive control applied to a team of hovercraft floating on an air hockey table. The hovercraft collectively solve a centralized optimal control problem in each sampling step via a stabilizing decentralized real-time iteration scheme using the alternating direction method of multipliers. The efficient implementation does not require a central coordinator, executes onboard the hovercraft, and facilitates sampling intervals in the millisecond range. The formation control experiments showcase the flexibility of the approach on scenarios with point-to-point transitions, trajectory tracking, collision avoidance, and moving obstacles.
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