Consensus_FI-D-20-00186.pdf (541.91 kB)
Event-triggered output consensus disturbance rejection algorithm for multi-agent systems with time-varying disturbances
journal contributionposted on 2021-10-18, 13:19 authored by Jiankun Sun, Jun YangJun Yang, Shihua Li, Xiangyu Wang, Guipu Li
This study investigates the problem of event-triggered output consensus disturbance rejection for multi-agent systems subject to time-varying disturbances. By virtue of the reduced-order generalized proportional-integral observer (GPIO) technique, a new output consensus disturbance rejection protocol is developed based on the measurement outputs. Taking the limited communication bandwidth into account, the multi-agent system closes the loop under the proposed consensus protocol only when a distributed event-triggering mechanism decides to transmit agent's current output to its neighbors. The proposed output consensus protocol can effectively enhance the robustness against the time-varying disturbances and save the communication resource, since the time-varying disturbances are accurately estimated and compensated. Furthermore, the proposed consensus algorithm does not require continuous communication among the neighboring agents and can successfully avoid the Zeno phenomenon. Finally, the numerical simulation results are presented to verify the effectiveness of the proposed output consensus protocol.
National Natural Science Foundation of China under Grant 61973081, Grant 61973080, and Grant 61873060
Natural Science Foundation of Jiangsu Province under Grant BK20190061
Post-Doctoral Innovation Talent Support Program of China under Grant BX20200140
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering
Published inJournal of the Franklin Institute
Pages12870 - 12885
- AM (Accepted Manuscript)
Rights holder© The Franklin Institute
Publisher statementThis paper was accepted for publication in the journal Journal of the Franklin Institute and the definitive published version is available at https://doi.org/10.1016/j.jfranklin.2020.04.014.
DepositorDr Jun Yang. Deposit date: 15 October 2021
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