Fangfei Cao

Beihang University, Beijing Institute of Technology

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About

Fangfei Cao is a researcher specializing in adaptive control systems, robotics, and intelligent trajectory planning, with a particular focus on complex, real-world applications. Her work bridges theoretical modeling and practical control, notably through the development of adaptive boundary controllers for undersea detection robots. In her highly cited 2018 paper (29 citations), she pioneered a partial differential equation (PDE) model using Hamilton’s principle to address actuator faults, unknown disturbances, and boundary deflection constraints in arm-string systems—a critical contribution to the reliability of autonomous underwater vehicles. More recently, Cao has advanced reinforcement learning-based control, designing a trajectory planning algorithm for manipulators operating in constrained spaces (2023). Her research demonstrates a clear trajectory from foundational PDE-based control theory to cutting-edge AI-driven robotics, highlighting her versatility in tackling both analytical and computational challenges. With growing citation impact, Cao’s work is increasingly influential in the fields of nonlinear control, fault-tolerant systems, and intelligent automation, offering practical solutions for industrial and exploratory robotics.