Papers
2
Total Citations
89
H-Index
2
About
Dr. Engang Tian is a leading figure in the field of cyber-physical systems and nonlinear control theory, with a particular focus on security and resource optimization. His research masterfully integrates advanced event-triggered mechanisms, sliding-mode control, and fuzzy logic to address critical challenges in networked environments. A landmark contribution is his 2024 work on "Dynamic-Memory Event-Triggered Sliding-Mode Secure Control," which has already garnered 79 citations for its pioneering approach to defending nonlinear semi-Markov jump systems against sophisticated stochastic cyber attacks, including denial-of-service and data injection threats. In this work, he employs Takagi-Sugeno fuzzy models to handle system nonlinearities while developing a novel dynamic-memory event-triggered strategy that conserves network resources without sacrificing security. Further demonstrating his versatility, Dr. Tian has also advanced optimal tracking control for unknown nonlinear systems, using a particle swarm optimization-driven reinforcement learning approach boosted by fuzzy modeling. His work is characterized by its practical relevance, addressing real-world constraints like limited bandwidth and unavailable system dynamics, making him a vital contributor to the next generation of resilient, intelligent control systems.
Research Focus
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Top Papers
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