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About

Zeyan Hu is a robotics researcher whose work focuses on the dynamic modeling and control of self-balancing and specialized robotic systems. His primary research areas include nonlinear control theory, adaptive control, and the application of neural networks to robotic stabilization. Hu’s major contributions lie in the design and implementation of controllers for inherently unstable platforms, such as unicycle and two-wheeled self-balancing robots. His most cited work, “Design of LQR and PID controllers for the self balancing unicycle robot” (15 citations), presents a comprehensive approach to achieving both pitching and rolling balance through coordinated motor and weight actuation. This foundational study is complemented by his work on two-wheeled robots (10 citations), where he employed Lagrangian dynamics and partial feedback linearization for controller synthesis. Hu has also explored more exotic mechanisms, including wire-moving robots inspired by tightrope walkers, and angular servo robots utilizing RBF neural network adaptive control. His research demonstrates a consistent focus on bridging theoretical control methods with practical robotic applications, providing a valuable resource for students and engineers working on mobile robotics and stabilization challenges.