Shufan Li
Papers
2
Total Citations
51
H-Index
2
About
Shufan Li is a rising researcher in the field of nonlinear stochastic systems and networked control, with a focus on the stabilization of complex, highly nonlinear delayed stochastic networks. Their work addresses critical challenges in control theory by developing innovative event-triggered and self-triggered strategies that reduce communication and computation burdens without sacrificing system stability. In their highly cited 2022 paper, Li introduced a stochastic event-triggered control mechanism for synchronizing hybrid switching diffusion networks, earning 29 citations for its practical relevance. Their 2024 contribution, already garnering 22 citations, marks a significant breakthrough by removing the restrictive linear growth condition for the first time in the stabilization of highly nonlinear delayed stochastic networks. Using a periodic self-triggered intermittent sampled-data approach, Li’s work provides rigorous yet implementable stabilization conditions. These achievements demonstrate Li’s ability to push the boundaries of nonlinear control theory, offering elegant solutions that are both theoretically deep and applicable to real-world networked systems. Their research is essential reading for scholars working on advanced stochastic control, event-triggered systems, and complex network dynamics.
Research Focus
Key Achievements
Top Papers
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