Dr. Xiuyun Zhang | Control Systems Engineering | Best Researcher Award

Published on by Superior Awards

Dr. Xiuyun Zhang | Control Systems Engineering | Best Researcher Award

Dr. Xiuyun Zhang | Tianjin University of Technology and Education | China

Dr. Xiuyun Zhang is a lecturer and researcher specializing in motor systems and their control, with a particular emphasis on multi-motor collaborative control. Her teaching covers theoretical foundations such as circuit principles and automatic control principles, while her research explores torque coordination in large-load drives, speed coordination in industrial applications, and position coordination and contour control in high-precision CNC machining. She has published over 20 SCI/EI indexed papers and more than 10 journal publications, with a record of 972 citations from 914 documents, 94 published works, and an h-index of 16. Her innovative contributions are reflected in 16 granted or filed patents, including invention and utility model patents. As a project leader, she has directed research supported by the Tianjin Natural Science Foundation Youth Project, the Tianjin Higher Education Science and Technology Development Fund, an invention patent conversion initiative, and several horizontal projects, while also contributing as a main researcher to a National Natural Science Foundation general project. With more than five completed or ongoing research projects, her work focuses on developing predictive and interactive control strategies that use speed and current as internal system variables, aiming to improve collaborative control accuracy and dynamic response in advanced motor applications.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

  • Zhang, R., Zong, Q., Zhang, X., Dou, L., & Tian, B. (2022). Game of drones: Multi-UAV pursuit-evasion game with online motion planning by deep reinforcement learning. IEEE Transactions on Neural Networks and Learning Systems, 34(10), 7900–7909.

  • Wang, D., Zong, Q., Tian, B., Shao, S., Zhang, X., & Zhao, X. (2018). Neural network disturbance observer-based distributed finite-time formation tracking control for multiple unmanned helicopters. ISA Transactions, 73, 208–226.

  • Dou, L., Cai, S., Zhang, X., Su, X., & Zhang, R. (2022). Event-triggered-based adaptive dynamic programming for distributed formation control of multi-UAV. Journal of the Franklin Institute, 359(8), 3671–3691.

  • Liu, D., Dou, L., Zhang, R., Zhang, X., & Zong, Q. (2022). Multi-agent reinforcement learning-based coordinated dynamic task allocation for heterogeneous UAVs. IEEE Transactions on Vehicular Technology, 72(4), 4372–4383.

  • Ye, L., Zong, Q., Tian, B., Zhang, X., & Wang, F. (2017). Control-oriented modeling and adaptive backstepping control for a nonminimum phase hypersonic vehicle. ISA Transactions, 70, 161–172.

  • Zhang, X., Zong, Q., Dou, L., Tian, B., & Liu, W. (2020). Finite-time attitude maneuvering and vibration suppression of flexible spacecraft. Journal of the Franklin Institute, 357(16), 11604–11628.

  • Zhang, X., Zong, Q., Dou, L., Tian, B., & Liu, W. (2020). Improved finite-time command filtered backstepping fault-tolerant control for flexible hypersonic vehicle. Journal of the Franklin Institute, 357(13), 8543–8565.

 

 

Dr. Mingwei Zhao | Electrical Engineering | Excellence in Research Award

Published on by Superior Awards

Dr. Mingwei Zhao | Electrical Engineering | Excellence in Research Award

Dr. Mingwei Zhao , Jiangsu Normal University & Shanghai University , China.

Dr. Mingwei Zhao 🎓, born in Shandong, China 🇨🇳, is a dedicated researcher and educator in the field of electrical engineering ⚡. He currently serves as a Lecturer at Jiangsu Normal University 🏫, specializing in power electronics and robotic systems 🤖. With a strong foundation in mechanical and electrical integration 🔧, he pursued advanced studies in power drive systems and control science 🎛️. His ongoing research is focused on innovative power electronic drive technologies and intelligent robotics 💡. Dr. Zhao’s work contributes significantly to automation and energy efficiency solutions in modern engineering 🌐.

Professional Profile

Scopus

Education & Experience

  • 🎓 B.S. in Mechanical and Electrical Integration, Nanjing University of Science and Technology, 2004

  • 🎓 M.S. in Power Electronics and Power Drive, Nanjing University of Aeronautics and Astronautics, 2012

  • 🎓 Ph.D. (in progress) in Control Science and Engineering, Shanghai University, since 2016

  • 👨‍🏫 Lecturer, School of Electrical Engineering and Automation, Jiangsu Normal University

Summary Suitability

Dr. Mingwei Zhao is a highly dedicated and innovative researcher, making him a strong candidate for the Excellence in Researcher Award. With a solid academic foundation and over a decade of hands-on experience, Dr. Zhao has significantly advanced the fields of power electronics drive technologies and robotic systems through both applied research and academic leadership.

Professional Development

Dr. Zhao has continually expanded his expertise through rigorous academic pursuits and hands-on teaching experience 👨‍🔬. Currently undertaking his Ph.D. at Shanghai University 🎓, he stays at the forefront of technological innovation by integrating control systems and robotics into his curriculum 🤖📘. His involvement in both academic and applied research ensures that his contributions are both theoretically sound and practically relevant 🛠️. As a Lecturer, he mentors students and fosters a dynamic learning environment 🎤💡. His professional development reflects a balanced focus on research, teaching, and practical implementation in modern automation systems 🚀.

Research Focus

Dr. Zhao’s research is centered in the Electrical and Automation Engineering category ⚙️, with a specialized emphasis on power electronic drive systems ⚡ and robotic control integration 🤖. He explores the design and control of energy-efficient power systems, automation technology, and intelligent robotic operations 🔋🔍. His current studies contribute to advancing smart drive technologies that are vital for automation and Industry 4.0 initiatives 🏭💡. By leveraging multidisciplinary principles, he aims to develop sustainable and intelligent engineering systems that enhance the performance and adaptability of electrical devices 🌱🧠.

Publication Top Notes

  • Title:
    An Open-Circuit Fault Diagnosis for Three-Phase PWM Rectifier Without Grid Voltage Sensor Based on Phase Angle Partition

  • Authors:
    Mingwei Zhao, et al.

  • Journal:
    IEEE Transactions on Circuits and Systems I: Regular Papers

  • Publisher:
    IEEE (Institute of Electrical and Electronics Engineers)

  • Year:
    2024

  • Citations:
    4 (as of the latest count)

  • Summary:
    This article presents a fault diagnosis method for three-phase PWM rectifiers that eliminates the need for a grid voltage sensor. It uses phase angle partitioning to detect open-circuit faults efficiently, enhancing system reliability.

Conclusion

Dr. Zhao’s pioneering efforts and sustained contributions to power electronics and robotics make him a worthy nominee for the Excellence in Researcher Award. His blend of theoretical expertise, practical engineering solutions, and educational leadership continues to push the boundaries of automation and intelligent systems, benefiting both academia and industry.