Papers
31
Total Citations
1,183
H-Index
19
About
Guangdeng Zong is a prominent control systems researcher whose work spans nonlinear control theory, stochastic switching systems, and intelligent adaptive control. His research has made substantial contributions to several interconnected areas, including finite-time stability analysis, sliding mode control (SMC), semi-Markov switching systems, and neural network-based adaptive control. Among his most influential contributions is pioneering work on finite-time tracking control for nonholonomic systems, which has accumulated 107 citations since 2005, alongside equally impactful recent research on adaptive neural dynamic-memory event-triggered control incorporating deferred output constraints. His sustained engagement with semi-Markov switching systems — addressing quantized measurements, stochastic disturbances, and asynchronous control modes — has significantly advanced robust control design for complex, real-world dynamical systems, with multiple papers in this domain each exceeding 50 citations. Zong's more recent contributions demonstrate a compelling evolution toward intelligent control strategies, integrating radial basis function neural networks, funnel-based prescribed performance methods, and dynamic event-triggered mechanisms to achieve fixed-time and asymptotic tracking guarantees. His work consistently bridges theoretical rigor with practical relevance, including applications to robotic arm systems and switched mechanical systems. With over a dozen highly cited papers spanning nearly two decades, Zong has established himself as a leading voice in advanced nonlinear and stochastic control engineering.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10