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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.