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Guodong Shi

Researcher at University of Sydney

Publications -  222
Citations -  3869

Guodong Shi is an academic researcher from University of Sydney. The author has contributed to research in topics: Node (networking) & Consensus. The author has an hindex of 28, co-authored 203 publications receiving 3223 citations. Previous affiliations of Guodong Shi include Royal Institute of Technology & Chinese Academy of Sciences.

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Reaching an Optimal Consensus: Dynamical Systems That Compute Intersections of Convex Sets

TL;DR: This paper establishes several important properties of the distance functions with respect to the global optimal solution set and a class of invariant sets with the help of convex and non-smooth analysis.
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Global target aggregation and state agreement of nonlinear multi-agent systems with switching topologies

TL;DR: With the help of graph theory and convex analysis, coordination conditions are obtained in some important cases, and the results show that simple local rules can make the networked agents with first-order nonlinear individual dynamics achieve desired collective behaviors.
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A Distributed Algorithm for Economic Dispatch Over Time-Varying Directed Networks With Delays

TL;DR: An algorithm based on the gradient push-sum method is proposed to solve the EDP in a distributed manner over communication networks potentially with time-varying topologies and communication delays.
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Behaviors of networks with antagonistic interactions and switching topologies

TL;DR: It is proven that, the limits of all the nodes states exist, and the absolute values of the node states reach consensus if the switching interaction graph is uniformly jointly strongly connected for unidirectional topologies, or infinitely jointly connected for bidirectionalTopologies.
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Event-Triggered Pinning Control of Switching Networks

TL;DR: This paper investigates event-triggered pinning control for the synchronization of complex networks of nonlinear dynamical systems described by time-varying weighted graphs and featuring generic linear interaction protocols.