A network transformation mapping divides the communication graph into reachable and unreachable parts at each instant, enabling asymptotic synchronization by ensuring convergence amplitude during reachable intervals exceeds divergence during unreachable ones.
Human-in-the-loop fuzzy iterative learning control of consensus for unknown mixed-order nonlinear multi- agent systems
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A Network Transformation Mapping Approach to Synchronization of Multi-Agent Systems With Disconnected Switching Topologies
A network transformation mapping divides the communication graph into reachable and unreachable parts at each instant, enabling asymptotic synchronization by ensuring convergence amplitude during reachable intervals exceeds divergence during unreachable ones.