Dr. Fazhi Song, a Professor at the Harbin Institute of Technology specializing in control science, motion control, and precision engineering, is an accomplished researcher whose work advances high-end manufacturing and ultra-precision motion systems. He holds advanced degrees culminating in a Ph.D. in Control Science and Engineering, with academic training focused on system identification, learning control, and precision motion technologies. Throughout his professional career, he has led major research initiatives in motion generation, performance control, and accuracy retentivity for advanced manufacturing equipment, contributing to national and provincial projects and collaborating with leading industrial partners on precision motion systems. His research centers on high-precision mechanical servo systems, uncertainty-robust learning control, multi-DOF motion coordination, and advanced control strategies for lithography-level equipment, supported by a strong record of publications, patents, and technical innovations. He has authored numerous peer-reviewed articles, contributed to an academic monograph, and advanced methodologies widely cited in the fields of precision engineering and automation, reflected through 45 citations, 9 documents, and an h-index of the candidate. His achievements include significant awards from national academic societies recognizing technological innovation, along with contributions as a guest editor for respected journals, session chair for international conferences, and active membership in IEEE and major professional automation and instrumentation societies. Dr. Song’s leadership in research, editorial service, and professional engagement underscores his commitment to advancing ultra-precision control technologies and cultivating scientific excellence in the global engineering community.
Profiles: Scopus | ORCID
Featured Publications
Song, Fazhi, A compensation method for electromagnetic hysteresis: Application in linear reluctance actuator. J. Magn. Magn. Mater., 2025.*
Song, Fazhi, Crest factor minimization of multisine signals based on the Chebyshev norm approximation method: With application to wafer stage FRF identification. Results Eng., 2025.*
Song, Fazhi, Identification for Precision Mechatronics: An Auxiliary Model-Based Hierarchical Refined Instrumental Variable Algorithm. Int. J. Robust Nonlinear Control., 2025.*
Song, Fazhi, Beyond Performance of Learning Control Subject to Uncertainties and Noise: A Frequency-Domain Approach Applied to Wafer Stages. IEEE/CAA J. Autom. Sinica., 2025, 5 citations.*