Dr. Wang Xiao

Time:2024-11-15Views:10

Dr. Wang Xiao


Lecturer

Director of Automation Research Lab

Email: w_xiao@buct.edu.cn



Background                                                                  

Dr. Xiao Wang, obtained Phd degree in spacecraft design from Beihang University. The current primary research interests include spacecraft dynamics and control, multi-agent game confrontation, etc. In recent years, extensive preliminary research on the typical space pursuit-evasion and pursuit-evasion-defense scenarios under incomplete environmental information has been conducted, employing methods such as orbital dynamics, fuzzy reasoning, reinforcement learning, among others. The publications are mainly about the field of orbital games, involving journals like IEEE Transactions on Aerospace and Electronic Systems and Neurocomputing. In recent, a heterogeneous cluster satellite simulation platform, which performs the “cloud-edge-end” pattern is built.

Areas of Research of Expertise

  • spacecraft dynamics and control

  • multi-agent game confrontation

Teaching  

Undergraduate Teaching

  • Automatic Control Theory

Postgraduate Teaching

  • Intelligent Control: Theory and Practice

Five Representative Publications     

[1] Wang X. , Shi P. , Wen C.  and Zhao Y. Design of Parameter-Self-Tuning Controller Based on Reinforcement Learning for Tracking Noncooperative Targets in Space[J]. IEEE Transactions on Aerospace and Electronic Systems, 56(6): 4192-4208, Dec. 2020, doi: 10.1109/TAES.2020.2988170. (SCI)

[2]Wang X , Shi P , Schwartz H , et al. An algorithm of pretrained fuzzy actor–critic learning applying in fixed-time space differential game[J]. Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering, 2021, 235(14):2095-2112. (SCI)

[3] Wang X, Li D, Bioinspired Actor-Critic Algorithm for Reinforcement Learning Interpretation with Levy-Brown Hybrid Exploration Strategy, Neurocomputing, 2024, 574(Mar.14):1.1-1.16. (SCI)

[4] Wang, X., Ma, Z., Cao, L. et al. A planar tracking strategy based on multiple-interpretable improved PPO algorithm with few-shot technique. Sci Rep, 2024, 14: 3910. https://doi.org/10.1038/s41598-024-54268-6. (SCI)

[5]  Xiao Wang, Zhuo Yang, Yuying Han, Hao Li, Peng Shi,Method of sequential intention inference for a space target based on meta-fuzzy decision tree, Advances in Space Research,2024,,ISSN 0273-1177,https://doi.org/10.1016/j.asr.2024.06.049. (SCI)