Muxun Xu

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About

Muxun Xu is a robotics researcher whose work focuses on advancing motor control systems for legged robots, particularly through the development of high-performance joint drive technologies. His key research areas include field-programmable gate array (FPGA)-based control architectures, torque predictive control, and permanent magnet servo motor optimization. In his most notable work, "Field Programmable Gate Array Based Torque Predictive Control for Permanent Magnet Servo Motors" (2022), Xu proposed a direct torque control method using a prediction model to enhance the dynamic performance of the inner-most torque/current control loop—a critical factor for the capabilities of whole joint systems in legged robots. This contribution addresses the growing demand for precise and responsive joint drives, directly impacting the agility and stability of robotic locomotion. With 3 citations, his paper has already garnered attention from peers working on motor control and robotics. Xu’s research bridges the gap between theoretical control algorithms and practical hardware implementation, offering a pathway to more efficient and powerful robotic systems. His work is particularly relevant for students and researchers exploring real-time control, FPGA applications, and the mechanical-electrical integration in advanced robotics.