In this paper we introduce the framework of Partial difference Equations (PdEs) over graphs for analyzing the behavior of multi-agent systems equipped with decentralized control schemes. Both leaderless and leader-follower models are considered. PdEs mimic Partial Differential Equations (PDEs) on graphs and can be studied by introducing concepts of functional analysis strongly inspired to the corresponding ones arising in PDEs theory. We generalize different models proposed in the literature by introducing errors in the agent dynamics and analyze agent coordination through the joint use of PdEs and automatic control tools. Moreover, for the simplest control schemes, we show that the resulting PdEs enjoy properties that are similar to those of well-known PDEs like the heat equation, thus allowing to exploit physical-based reasoning for conjecturing formation properties.

Analysis of coordination in multi-agent systems through partial difference equations

FERRARI TRECATE, GIANCARLO;
2006-01-01

Abstract

In this paper we introduce the framework of Partial difference Equations (PdEs) over graphs for analyzing the behavior of multi-agent systems equipped with decentralized control schemes. Both leaderless and leader-follower models are considered. PdEs mimic Partial Differential Equations (PDEs) on graphs and can be studied by introducing concepts of functional analysis strongly inspired to the corresponding ones arising in PDEs theory. We generalize different models proposed in the literature by introducing errors in the agent dynamics and analyze agent coordination through the joint use of PdEs and automatic control tools. Moreover, for the simplest control schemes, we show that the resulting PdEs enjoy properties that are similar to those of well-known PDEs like the heat equation, thus allowing to exploit physical-based reasoning for conjecturing formation properties.
2006
The AI, Robotics & Automatic Control category is concerned with resources on the research and techniques of artificial intelligence; that is, the creation of machines that exhibit characteristics of human intelligence (e.g., efficient representation of knowledge, reasoning, deduction, problem solving, heuristics, and analysis of contradictory or ambiguous information). Related AI technologies include expert systems, fuzzy systems, natural language processing, speech and pattern recognition, computer vision, decision-support systems, knowledge-bases, and neural networks. Robotics resources are concerned with the design, construction, and operation of robots. Automatic Control resources cover the design and development of regulating processes and systems that replace the necessity of human intervention. Topics include adaptive control, robust control, discrete-event control, dynamic control, fuzzy control, and optimal control. Cybernetics resources are concerned with the control and communication within and between artificial (machine) systems and living or natural systems.
Sì, ma tipo non specificato
Inglese
Internazionale
STAMPA
51
6
1058
1063
Multi-agent systems; consensus problems; partial difference equations; leader-following; collision avoidance
3
info:eu-repo/semantics/article
262
FERRARI TRECATE, Giancarlo; A., Buffa; M., Gati
1 Contributo su Rivista::1.1 Articolo in rivista
none
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/107879
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