Chung‐Wen Hung

National Yunlin University of Science and Technology, National Formosa University

Papers

Total Citations

H-Index

About

Chung-Wen Hung is a leading researcher in advanced motor control and industrial automation systems, with a particular focus on multi-motor synchronization and embedded intelligence. His most impactful work, "Multi-Motor Synchronous Control with CANopen" (2019, 7 citations), addresses a critical challenge in robotics and automated production lines by developing a Brushless DC (BLDC) motor synchronization system using the CANopen protocol—a key contribution for applications requiring precise, coordinated motion. Hung has further advanced the field through his innovative integration of deep learning on microcontrollers, as demonstrated in "Device Light Fingerprints Identification Using MCU-Based Deep Learning Approach" (2021, 3 citations), which introduces a novel method for device identification by analyzing subtle spectral variations in lighting equipment. His practical engineering contributions extend to high-precision manufacturing, including system integration for aerospace production lines (2021) and EtherCAT-based delta robot synchronous control (2022). Hung’s work bridges the gap between theoretical control algorithms and real-world industrial deployment, making him a valuable resource for students and researchers exploring synchronous motor control, embedded AI, and Industry 4.0 automation technologies.