庞逸鹏，长聘教授、博士生导师，国家高层次青年人才。主要从事多智能体系统、分布式优化、博弈控制等领域的研究，方向包括分布式优化、在线优化、非合作博弈、集群博弈及其在无人系统中的应用。

【教育与工作经历】

2020年，获得新加坡南洋理工大学哲学博士学位，随后在新加坡南洋理工大学电子电机工程学院担任博士后研究员。2026年，入职南京航空航天大学自动化学院。

【招生信息】

每年招收硕士生3名、博士生2名。欢迎对多智能体系统、分布式优化、博弈论及无人系统协同控制等方向感兴趣的同学尽早邮件联系。要求数学基础扎实、编程能力突出，具有优化理论、控制算法设计、无人系统仿真或ROS开发经验者优先。课题组提供系统的学术指导与充足的科研经费，优秀者可推荐至国内外名校学习和深造。

【学术成果】

部分成果列举如下：

[1] Chunhe Ma, Zhi Feng, Shuo Feng, Yipeng Pang, Guoqiang Hu, “Viscosity Solutions of Hamilton-Jacobi-Bellman Equations for Nonzero-Sum Differential Games with Safety Consideration,” IEEE Transactions on Automatic Control, 2026.

[2] Yipeng Pang, Guoqiang Hu, “Randomized Gradient-Free Distributed Online Optimization via a Dynamic Regret Analysis,” IEEE Transactions on Automatic Control, vol. 68, no. 11, pp. 6781-6788, 2023.

[3] Yipeng Pang, Guoqiang Hu, “Nash Equilibrium Seeking in N-Coalition Games via a Gradient-Free Method,” Automatica, vol. 136, pp. 110013, 2022.

[4] Yipeng Pang, Guoqiang Hu, “Gradient-Free Distributed Optimization with Exact Convergence,” Automatica, vol. 144, pp. 110474, 2022.

[5] Yipeng Pang, Guoqiang Hu, “A Gradient-Free Distributed Optimization Method for Convex Sum of Non-Convex Cost Functions,” International Journal of Robust and Nonlinear Control, vol. 32, no. 14, pp. 8086-8101, 2022.

[6] Yipeng Pang, Guoqiang Hu, “Distributed Nash Equilibrium Seeking with Limited Cost Function Knowledge via A Consensus-Based Gradient-Free Method,” IEEE Transactions on Automatic Control, vol. 66, no. 4, pp. 1832-1839, 2021.

[7] Yipeng Pang, Guoqiang Hu, “Randomized Gradient-Free Distributed Optimization Methods for a Multi-Agent System with Unknown Cost Function,” IEEE Transactions on Automatic Control, vol. 65, no. 1, pp. 333-340, 2020.

个人主页：https://faculty.nuaa.edu.cn/pangyipeng/zh_CN/index.htm