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King Yuan is a control systems researcher whose work has made significant contributions to the fields of robotic manipulation, nonlinear control theory, and flexible joint robotics. Active primarily in the late 1980s and early 1990s, Yuan's research focused on developing sophisticated mathematical frameworks for controlling complex robotic systems, drawing on differential geometric nonlinear control theory and Lagrangian mechanics. Among his most influential contributions is his work on robust nonlinear control strategies for robotic manipulators with nonlinear actuator dynamics (1990, 29 citations), which introduced a two-stage control scheme capable of handling both nominal and perturbed system conditions. Equally notable is his application of external linearization to flexible joint robot control (1990, 28 citations), achieving input-output decoupling through feedback linearization — a technically elegant solution to a challenging robotics problem. Yuan also advanced the modeling of flexible robotic manipulators using a Lagrange-Euler-assumed modes formulation (1988, 20 citations), providing a general and explicit framework not previously available in the literature. His broader theoretical contributions include characterizing allowable perturbations for robust decoupling in affine nonlinear systems and feedback stabilization of Hamiltonian control systems, cementing his reputation as a rigorous and innovative thinker in advanced control engineering.