The paper presents new results on asymptotic consensus for continuous time non-autonomous nonlinear networks under almost-periodic interactions. We treat consensus variables that are different than those affecting network's connectivity and allow the former to track an estimate of the average magnitude of a measured field despite the presence of limited agents' interaction (herein represented by almost periodic connectivity). To this end, a suitable notion of integral connectivity is introduced, frozen in state variables, and of simple verification, without requiring monotonicity of interactions (viz. network's cooperativity). An application of the proposed results is illustrated considering a representative example in the scenario of autonomous sampling by mobile robots.
Consensus of time-varying nonlinear non-autonomous networks with application to field sampling by mobile robots / Manfredi, Sabato; Angeli, D.. - 2016-:(2016), pp. 4848-4853. (Intervento presentato al convegno 54th IEEE Conference on Decision and Control, CDC 2015 tenutosi a Osaka International Convention Center (Grand Cube), 5-3-51 Nakanoshima, Kita-Ku, jpn nel 2015) [10.1109/CDC.2015.7402976].
Consensus of time-varying nonlinear non-autonomous networks with application to field sampling by mobile robots
MANFREDI, SABATO;
2016
Abstract
The paper presents new results on asymptotic consensus for continuous time non-autonomous nonlinear networks under almost-periodic interactions. We treat consensus variables that are different than those affecting network's connectivity and allow the former to track an estimate of the average magnitude of a measured field despite the presence of limited agents' interaction (herein represented by almost periodic connectivity). To this end, a suitable notion of integral connectivity is introduced, frozen in state variables, and of simple verification, without requiring monotonicity of interactions (viz. network's cooperativity). An application of the proposed results is illustrated considering a representative example in the scenario of autonomous sampling by mobile robots.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
