Hong‐Sheng Wu

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About

Hong-Sheng Wu is a leading researcher in advanced motion control and intelligent robotic systems, with a focus on fractional-order control strategies and neural network integration. His most notable contribution is the development of a Fuzzy Neural LSTM-RBLS framework for fractional-order PID sliding-mode motion control, specifically applied to autonomous mobile robots equipped with four independent steering and independent driving (ISID) wheels. This work, published in 2024, has already garnered 2 citations, signaling its early impact on the field of precision robotics and adaptive control. Wu’s research bridges the gap between classical control theory and modern machine learning, offering robust solutions for complex, nonlinear dynamics in autonomous navigation. His innovative approach enhances system stability, trajectory tracking, and disturbance rejection, making it highly relevant for real-world applications in logistics, manufacturing, and service robotics. By combining fuzzy logic, long short-term memory networks, and radial basis functions, Wu has set a new benchmark for intelligent motion control, positioning himself as a rising authority in the intersection of robotics, control engineering, and artificial intelligence.