On designing event-based consensus protocols for nonlinear multi-agent systems

This paper addresses an event-based consensus problem for a continuous-time nonlinear multi-agent system subject to communication resource constraints. The agents' states are measured by a multi-sensor network, in which sensor nodes are dispersedly deployed in a sensor field. Each sensor node c...

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Bibliographic Details
Published inIECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society pp. 5392 - 5397
Main Authors Xiaohua Ge, Qing-Long Han
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2016
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DOI10.1109/IECON.2016.7793692

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Summary:This paper addresses an event-based consensus problem for a continuous-time nonlinear multi-agent system subject to communication resource constraints. The agents' states are measured by a multi-sensor network, in which sensor nodes are dispersedly deployed in a sensor field. Each sensor node can gather information from its neighboring nodes, process aggregated information by a prescribed network topology, sample processed information at a synchronous sampling period and then transmit sampled information to a remote controller node via a shared network medium. First, to reduce the frequency of transmitting sensors' sampled-data, an event-based communication strategy is presented to schedule sensors' data transmission. Second, based on transmitted aggregated measurement, a delicate event-based consensus protocol is proposed. Compared with some existing event-based consensus protocols based on transmitted local measurement, the proposed protocol offers some advantages. Third, a criterion for designing desired event-based consensus protocol and event triggering strategy is provided such that the proposed event-based consensus is achieved. It is shown that the consensus protocol gain and the event strategy threshold parameter can be jointly determined by solving a Riccati inequality. Finally, a vertical taking-off and landing aircraft model is employed to show the effectiveness of the proposed result.
DOI:10.1109/IECON.2016.7793692