**Intervenant : **Dimitris BOSKOS, KTH

**Lieu : ** Salle Direction B 3me etage

**Résumé : ** p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px Helvetica} span.s1 {font-kerning: none}

**Title:** Distributed Control and Abstraction for Multi-Agent Systems

**Abstract:** High level planning for multi-agent systems constitutes a research area which has gained an emerging attention during the last two decades. While the agents' coordination is in principle based on the design of continuous interaction protocols, the synthesis of high level plans leverages discrete representations (abstractions) of their dynamic behavior and appropriate algorithmic tools.

In this talk we discuss the derivation of such abstractions for agent dynamics comprising of feedback interconnection terms and additive bounded inputs, which provide the ability for planning under the coupled constraints. These dynamics are also motivated by multi-agent coordination protocols which are robust with respect to the additional input part. We will present such a cooperative control framework, which guarantees that network connectivity is robustly maintained with respect to bounded additive inputs. Furthermore, a modification of the feedback design ensures forward invariance of the agents' trajectories inside a convex workspace, without affecting the obtained robustness bounds.

In order to derive the agents' distributed symbolic models, we determine space-time discretizations which establish that each agent's abstraction has at least one outgoing transition from every discrete state. The symbolic model of each agent is based on the knowledge of its neighbors' discrete positions and the transitions are performed through hybrid control laws, which can drive the agent to its possible successor states. As an extension of these results we also consider a varying degree of decentralization and build each abstract model based on discrete information up to a tunable distance in the communication graph. Finally, we discuss the derivation of online abstractions, by discretizing overapproximations of the agents' reachable sets over a bounded time horizon.

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