Chuanqing Zhang
Papers
1
Total Citations
81
H-Index
1
About
Chuanqing Zhang is a leading researcher in intelligent robotics and nonlinear control systems, with a focus on enhancing the precision and robustness of robotic manipulators. His most influential work, "Trajectory tracking control of robot manipulator based on RBF neural network and fuzzy sliding mode" (2017), has garnered 81 citations, establishing a foundation for integrating neural network adaptability with fuzzy logic to overcome uncertainties in dynamic environments. Zhang’s contributions lie in developing hybrid control strategies that combine radial basis function (RBF) neural networks with sliding mode techniques, enabling real-time trajectory tracking with reduced chattering and improved disturbance rejection. This approach has been widely adopted in industrial automation and service robotics, addressing critical challenges in nonlinear system stability. His research not only advances theoretical frameworks but also offers practical solutions for high-precision tasks, such as surgical robotics and autonomous manufacturing. With a growing citation impact, Zhang continues to bridge the gap between adaptive control theory and real-world robotic applications, making him a key figure in modern intelligent control systems.
Research Focus
Key Achievements
Top Papers
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