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• W3173801954 abstract "This brief studies the robust semiglobal multi-agent consensus with linear subsystems subject to nonidentical parameter uncertainties and input saturation. A distributed low-gain-based nonlinear feedback law that avoids eigenvalues of the Laplacian matrix is established. It is proved that under the provided procedure, semiglobal multi-agent consensus is achieved when the lower bound of input saturation and the upper bound of parameter uncertainties satisfy certain relationship, which is shown as a design constraint in the provided method. The event-triggered scenario of the proposed protocol is further studied; the designs for the control law and the updating rule based on node-based event-driven mechanisms are provided and analyzed." @default.
• W3173801954 created "2021-07-05" @default.
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• W3173801954 date "2022-02-01" @default.
• W3173801954 modified "2023-10-01" @default.
• W3173801954 title "Distributed Robust Semiglobal Consensus With Matched Uncertainties and Input Saturation" @default.
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• W3173801954 doi "https://doi.org/10.1109/tcsii.2021.3091630" @default.
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