Steering the dynamics of a multi-agent system towards a balanced circular formation is a paradigmatic ex-ample of formation control that attracted extensive research interest from the engineering community. The traditional estimation and control strategies typically relied on both accurate directional measurements and a thorough knowledge of the environment, which are seldom available in applications. Here, we consider a scenario where the information exchanged by the agents is limited, the measurement being uncertain and intermittent. Additionally, we do not assume that the number of agents composing the formation is known. In this uncertain environment, we propose an estimation and control strategy that leverages interval analysis to (i) estimate the size of the formation, (ii) estimate the relative distance among the agents, and (iii) achieve a balanced circular formation. The effectiveness of the strategy is demonstrated through extensive numerical simulations.
Formation Control of Multi-agent Systems in an Uncertain Environment / De Lellis, Pietro; Garofalo, Francesco; Lo Iudice, Francesco. - (2020), pp. 454-458. (Intervento presentato al convegno 2020 European Control Conference (ECC)) [10.23919/ECC51009.2020.9143997].
Formation Control of Multi-agent Systems in an Uncertain Environment
De Lellis, PietroPrimo
;Garofalo, Francesco;Lo Iudice, Francesco
2020
Abstract
Steering the dynamics of a multi-agent system towards a balanced circular formation is a paradigmatic ex-ample of formation control that attracted extensive research interest from the engineering community. The traditional estimation and control strategies typically relied on both accurate directional measurements and a thorough knowledge of the environment, which are seldom available in applications. Here, we consider a scenario where the information exchanged by the agents is limited, the measurement being uncertain and intermittent. Additionally, we do not assume that the number of agents composing the formation is known. In this uncertain environment, we propose an estimation and control strategy that leverages interval analysis to (i) estimate the size of the formation, (ii) estimate the relative distance among the agents, and (iii) achieve a balanced circular formation. The effectiveness of the strategy is demonstrated through extensive numerical simulations.File | Dimensione | Formato | |
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