教师主页
李启夫
李启夫
助理研究员
上海交通大写williamhill威廉希尔官网A424 qifuli@sjtu.edu.cn

教育背景

  • 2003年-2006年，美国北卡罗莱纳州立大学，博士
  • 1997年-1999年，哈尔滨工业大学，硕士
  • 1993年-1997年，哈尔滨工业大学，学士

工作经历

  • 2017年-至今，威廉体育williamhill官网，专职科研
  • 2010年-2016年，美国加利福尼亚州立大学长堤分校，讲师
  • 2012年-2014年，美国Cobalt Construction Co.，结构工程师（加州注册土木工程师）
  • 2007年-2010年，美国Scenario Design/KHS&S Contractors Inc.，结构工程师（加州注册土木工程师）
  • 1999年-2002年，新加坡南洋理工大学，研究助理

研究方向

  • 飞行器气动伺服弹性建模与控制；
  • 飞行安全增强控制；
  • 非常规构型飞行器动力学建模与控制；
  • 基于强化学习的飞行控制技术；

代表性论文专著

  • W. Gao, W. Jiang, Q. Li, and B. Lu, Linear parameter-varying model order reduction and control design of Flexop demonstrator aircraft, The Aeronautical Journal, accepted.
  • S. Yuan, Q. Li, B. Lu, et.al., Trajectory prediction for fighter aircraft ground collision avoidance based on the model predictive control technique, Aerospace Systems, 2025, 8: 61-70.
  • J. Wei, W. Gao, W. Gao, B. Lu, and Q. Li, Aerodynamic simulations of an electric vertical takeoff and landing aircraft using reformulated vortex particle method, Physics of Fluids, 2024, 36: 065114.
  • W. Gao, Y. Liu, Q. Li, and B. Lu, Gust load alleviation of a flexible flying wing with linear parameter-varying modeling and model predictive control, Aerospace Science and Technology, 2024, 155: 109671.
  • Y. Liu, X. Niu, Q. Li, and B. Lu, An improved linear parameter-varying modeling, model order reduction, and control design process for flexible aircraft, Aerospace Science and Technology, 2024, 144: 108765.
  • W. Gao, W. Jiang, B. Lu, and Q. Li, Flight control design for eVTOL aircraft using nonlinear dynamic inversion and Hinf control, ICGNC 2024, Changsha, China.
  • W. Jiang, W. Gao, B. Lu, and Q. Li, Aircraft braking control using an LMI-based linear parameter-varying PID method, ICGNC 2024, Changsha, China.
  • Y. Liu, W. Gao, Q. Li, and B. Lu, Oblique projection-based modal matching algorithm for LPV model order reduction of aeroservoelastic systems, Aerospace, 2023, 10: 406.
  • W. Gao, Y. Liu, Q. Li, and B. Lu, Aerodynamic modeling and simulation of multi-lifting surfaces based on the unsteady vortex lattice method, Aerospace, 2023, 10: 203.
  • X. Lang, F. Cen, Q. Li, and B. Lu, Deep reinforcement learning-based upset recovery control for generic transport aircraft, Aerospace Systems, 2022, 5: 625-634.
  • X. Niu, B. Lu, B. Feng, and Q. Li, Linear parameter-varying gain-scheduling preview-based robust attitude control design for a staring-mode satellite, Aerospace Science and Technology, 2022, 129: 107816.