Baomin Feng

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About

Baomin Feng is a robotics and control systems researcher whose work centers on advanced control strategies for space robotic systems. His research addresses one of the most challenging problems in aerospace engineering: achieving precise, reliable control of free-floating space robots operating under conditions of significant model uncertainty, external disturbances, and complex dynamics. Feng's most notable contributions lie in the development of intelligent and robust control frameworks for space manipulators. His 2005 paper introducing a Fuzzy Neural Network (FNN) controller for space robots — his most cited work with 15 citations — demonstrated that high-precision tracking could be achieved without the linear parameterization constraints required by conventional adaptive control methods. He further advanced the field by integrating radial-basis-function (RBF) neural networks for real-time uncertainty compensation and by developing chattering-free sliding mode controllers that address a longstanding limitation in robust control design. Across his publications, Feng consistently employs Lyapunov stability theory and dissipative theory to rigorously guarantee controller performance in Cartesian task space. With a body of work accumulating nearly 40 citations, his research provides practical and theoretically sound tools for engineers developing next-generation autonomous space robotics systems.