Tingting Cheng
Papers
4
Total Citations
106
H-Index
3
About
Dr. Tingting Cheng is a leading researcher in nonlinear control systems, specializing in secure consensus tracking and advanced robotic manipulation. Her work addresses critical challenges in multi-agent systems (MASs) under cyber threats, notably denial-of-service (DoS) attacks. In her highly cited 2023 paper (57 citations), she pioneered an event-triggered adaptive bipartite secure consensus scheme that ensures asymptotic tracking despite adversarial disruptions—a breakthrough for resilient networked systems. For flexible robotic manipulators, Dr. Cheng has developed singularity-free, command-filtered adaptive fuzzy finite-time control algorithms (26 citations, 2023) that overcome the "explosion of complexity" inherent in backstepping methods. Her event-triggered strategies (2021, 20+ citations) dramatically reduce communication frequency while maintaining asymptotic tracking performance, enhancing energy efficiency in real-world robots. By integrating adaptive fuzzy logic with event-triggered mechanisms, she has delivered practical solutions for systems with dead-zone inputs and model uncertainties. Dr. Cheng’s contributions are foundational for next-generation autonomous systems requiring both security and precision, earning her recognition as a rising authority in adaptive and event-triggered control theory.
Research Focus
Key Achievements
Top Papers
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