Yingtao Zhao

Beijing University of Chemical Technology, Harbin Institute of Technology

Papers

Total Citations

H-Index

About

Yingtao Zhao’s research focuses on the control and stabilization of nonholonomic mobile robots, particularly addressing the challenges of trajectory tracking and point stabilization. In his most-cited work (2010), Zhao introduced a mixed controller that integrates backstepping techniques with neural dynamics, using a virtual target point to seamlessly unify tracking and stabilization tasks—a novel approach that has garnered 9 citations. He further advanced the field by optimizing fuzzy control systems with genetic algorithms for wheeled mobile robot stabilization (2011, 3 citations). Zhao’s contributions lie in bridging theoretical control methods with practical robotic motion, offering elegant solutions to the inherent nonlinearities and constraints of nonholonomic systems. His work is particularly valuable for students and researchers in robotics and control engineering, as it demonstrates how hybrid control strategies can overcome classic limitations in mobile robot autonomy. While his citation counts reflect a focused niche, Zhao’s innovative use of neural dynamics and evolutionary optimization marks him as a thoughtful contributor to intelligent robotic control.