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About

Dr. Hongfu Yu is a leading researcher in advanced control systems and mechatronics, with a primary focus on electro-hydraulic servo systems and robotic excavators. His most impactful contribution is the development of an adaptive sliding mode controller integrated with Radial Basis Function (RBF) neural networks, published in 2022 and cited over 210 times—a landmark work that significantly improved the robustness and precision of electro-hydraulic systems under uncertain conditions. Dr. Yu has also made critical advances in system identification and nonlinear friction compensation, publishing two highly cited papers in 2019 (88 and 75 citations, respectively) that enable more accurate trajectory control and smoother operation of hydraulic machinery. His work on flexible virtual fixtures for human-excavator cooperative systems (28 citations) demonstrates a commitment to safe, intuitive human-robot interaction in heavy equipment. Additionally, his research on recursive least squares algorithms with forgetting factors provides a practical, rapid method for modeling electro-hydraulic proportional systems, directly supporting real-time control in robotic excavators. Through these contributions, Dr. Yu has established himself as a key figure in bridging neural network control theory with real-world hydraulic applications, with his work collectively cited over 400 times.