Haoran Fang
Papers
6
Total Citations
94
H-Index
6
About
Dr. Haoran Fang is a leading researcher in the advanced control of robotic systems, specializing in the intersection of adaptive neural networks, sliding mode control, and nonlinear dynamics. His work primarily addresses the critical challenges of uncertainty, input saturation, and state constraints in robotic manipulators and nonholonomic wheeled mobile robots. Dr. Fang’s major contributions include pioneering predefined-time and fixed-time convergence control schemes, which guarantee system stability within a user-specified timeframe regardless of initial conditions—a significant leap over traditional asymptotic methods. His most cited work, "Full-state constrained neural control and learning for the nonholonomic wheeled mobile robot with unknown dynamics" (2021, 27 citations), introduces a novel framework for safe, constraint-aware navigation. His 2022 paper on predefined-time sliding mode control (19 citations) further demonstrates his impact, offering a robust solution for manipulators with input saturation. With over 90 total citations, Dr. Fang’s research is widely recognized for its theoretical rigor and practical applicability, making him a key figure in the development of intelligent, high-performance robotic control systems.
Research Focus
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Top Papers
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