Guoqiang Zhu
Papers
2
Total Citations
12
H-Index
2
About
Guoqiang Zhu is a leading researcher in the control and autonomy of quadrotor unmanned aircraft robots (UARs), with a focus on adaptive, intelligent, and event-driven systems. His major contributions lie in developing neural network-based adaptive control schemes that address critical challenges in trajectory tracking, particularly under actuator constraints such as hysteresis. In his highly cited 2022 work, Zhu introduced an adaptive event-triggered control method that optimizes communication and computational resources while maintaining robust flight performance. Building on this, his 2024 study proposed an adaptive observer-based implicit inverse control technique, validated experimentally on the QDrone platform, to handle motor nonlinearities in real-world scenarios. Though his most-cited papers currently have 7 and 5 citations, their recency and experimental validation signal growing influence in the field. Zhu’s work bridges theoretical control design with practical implementation, offering scalable solutions for next-generation autonomous aerial systems. His research is particularly valuable for engineers and students working on resilient, resource-efficient drone control.
Research Focus
Key Achievements
Top Papers
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