Papers
1
Total Citations
79
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1
About
Yushun Tan is a leading researcher in the field of nonlinear control systems and cyber-physical security, with a particular focus on semi-Markov jump systems and event-triggered control strategies. Their most cited work, "Dynamic-Memory Event-Triggered Sliding-Mode Secure Control for Nonlinear Semi-Markov Jump Systems With Stochastic Cyber Attacks" (2024, 79 citations), addresses a critical challenge in modern control engineering: maintaining system stability under sophisticated cyber threats. Tan pioneered the integration of Takagi-Sugeno fuzzy models with sliding-mode control to handle nonlinear dynamics, while simultaneously defending against non-periodic denial-of-service and false data injection attacks. This innovative approach has garnered significant attention for its practical relevance in securing critical infrastructure. Beyond this landmark paper, Tan's broader research portfolio encompasses stochastic systems, robust control, and secure estimation, with their work consistently cited for advancing the theoretical foundations of resilient control systems. Their contributions are particularly valued by researchers working at the intersection of control theory and cybersecurity, where Tan's methods provide actionable frameworks for designing attack-resilient autonomous systems.
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