Homepage - Ran Zhou, Tsinghua University

Life Photo of Ran

Hello, I’m Ran Zhou. Since 2020, I have been pursuing a Ph.D. in Mechanical Engineering at the Institute of Mechatronic Engineering, Department of Mechanical Engineering, Tsinghua University, under the supervision of Prof. Chuxiong Hu. From Oct. 2023 to Dec. 2023, I was also a visiting student researcher at the Mechanical Systems Control Lab in the Department of Mechanical Engineering at UC Berkeley, supervised by Prof. Masayoshi Tomizuka. Prior to this, I graduated with a B.E. in Mechanical Engineering from Tsinghua University in 2020.

My research primarily focuses on precision/ultraprecision motion control, including intelligent feedforward control, predictive control, and neural network control with applications to practical precision/ultraprecision mechatronic systems.

Contact:
zhouran2000@gmail.com
zhour20@mails.tsinghua.edu.cn


Education

Department of Mechanical Engineering - Tsinghua University Beijing, China
Ph.D. in Mechanical Engineering Aug. 2020 - expected Jun. 2025
Ph.D. Supervisor: Prof. Chuxiong Hu


Department of Mechanical Engineering - University of California, Berkeley Berkeley, CA, USA
Visiting Student Researcher in MSC Lab Oct. 2023 - Dec. 2023
Supervisor: Prof. Masayoshi Tomizuka


Department of Mechanical Engineering - Tsinghua University Beijing, China
Bachelor in Mechanical Engineering Aug. 2016 - Jun. 2020
GPA: 3.87/4.0 (1/109)


Department of Computer Science and Engineering - Tsinghua University Beijing, China
Minor in Computer Application Sep. 2017 - Jun. 2020

Research Interests

  • Precision/ultraprecision motion control
  • Predictive control
  • Neural network control

Selected Publications

  1. R. Zhou, C. Hu, T. Ou, Z. Wang, and Y. Zhu, “Intelligent GRU-RIC Feedforward Compensation Control Method with Application to an Ultraprecision Motion Stage,” IEEE Trans. Ind. Inform., 2023, DOI: 10.1109/TII.2023.3331075. (SCI/EI, IF=12.3)

  2. R. Zhou, C. Hu, Z.Wang, S. He, and Y. Zhu, “Nonlinearity Compensation and High-Frequency Flexibility Suppression Based RIC Method for Precision Motion Control Systems,” IEEE Trans. Ind. Inform., vol. 19, no. 2, pp. 1332-1342, Feb. 2023. (SCI/EI, IF=12.3, ESI Highly Cited Paper)

  3. C. Hu, R. Zhou, Z. Wang, Y. Zhu, and M. Tomizuka, “Real-Time Iterative Compensation Framework for Precision Mechatronic Motion Control Systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 7, pp. 1218-1232, Jul. 2022. (SCI/EI, IF=11.8)

  4. R. Zhou, C. Hu, B. Hou, and Y. Zhu, “Comparative Study of Performance-Oriented Feedforward Compensation Strategies for Precision Mechatronic Motion Systems,” IEEE Access, vol. 10, pp. 100812-100823, 2022. (SCI/EI, IF=3.9)

  5. R. Zhou, C. Hu, Y. Zhu, and M. Zhang, “Model Prediction based Online Feedforward Compensation Control of Maglev Planar Motor with Comparative Investigation,” in IEEE Int. Conf. Mechatron. (ICM), Kashiwa, Japan, Mar. 2021, pp. 1-6. (EI, Oral Report)


Honors and Awards

  • National Scholarship for Postgraduates (Top 2%) - Dec. 2022
  • Second Prize in National College Mechanical Innovation Competetion - Oct. 2020
  • First Prize in Beijing College Mechanical Innovation Competetion - Sep. 2020
  • Tsinghua Future Scholar Scholarship - Aug. 2020
  • Tsinghua Outstanding Undergraduate Award (Top 2%) - Jun. 2020
  • Beijing Outstanding Undergraduate Award (Top 5%) - Jun. 2020
  • National Scholarship for Undergraduates (Top 2%) - Dec. 2019
  • Tsinghua Top Grade Scholarship for Undergraduates (The highest student honor with 10 winners per year in Tsinghua University) - Dec. 2019
  • Tsinghua Comprehensive Excellence Award (Top 7%) - Dec. 2019
  • Tsinghua Jiang Nanxiang Scholarship - Dec. 2018
  • Tsinghua Comprehensive Excellence Award (Top 7%) - Dec. 2018
  • Tsinghua Comprehensive Excellence Award (Top 7%) - Dec. 2017

Academic Service

  • Reviewer for IEEE Transactions on Cybernetics, IEEE Transactions on Industrial Informatics, IEEE Transactions on Industrial Electronics, IEEE/ASME Transactions on Mechatronics
  • Reviewer for Ocean Engineering
  • Reviewer for 2023 Modeling, Estimation and Control Conference (MECC 2023)