提出分布式算法计算多智能体系统可达集，支持动态与静态图。
An Algorithm for Distributed Computation of Reachable Sets for Multi-Agent Systems
- 基于多面体逼近思想，设计全分布式计算框架
- 在静态与受限时变图下均保证收敛性
- 适合需协同安全分析的分布式控制系统
本文研究多智能体系统（MASs）在无向、静态图结构下的分布式可达集计算问题。由于每个智能体的控制输入依赖自身状态及邻居状态，而系统动态常被个体隐藏，导致完全分布式计算可达集极具挑战。本文引入多面体可达集逼近方法，并将其推广至多智能体场景，以完全分布式方式建模子问题，给出了相应计算的收敛性证明。所提算法在两种情况下被证明收敛：一是静态智能体拓扑图，二是满足特定条件的时变图。
原文摘要 · Abstract (English)
In this paper, we consider the problem of distributed reachable set computation for multi-agent systems (MASs) interacting over an undirected, stationary graph. A full state-feedback control input for such MASs depends no only on the current agent's state, but also of its neighbors. However, in most MAS applications, the dynamics are obscured by individual agents. This makes reachable set computation, in a fully distributed manner, a challenging problem. We utilize the ideas of polytopic reachable set approximation and generalize it to a MAS setup. We formulate the resulting sub-problems in a fully distributed manner and provide convergence guarantees for the associated computations. The proposed algorithm's convergence is proved for two cases: static MAS graphs, and time-varying graphs under certain restrictions.
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