Name: Panlong Tan
Gender: Male
Department: Institute of Robotics and Automatic Information Systems
Title: Assistant research fellow
Education: Ph.D.
Major: Control Science and Engineering
Tel: 13682103327
E-mail: tanpl@nankai.edu.cn
Directions: Parafoil modeling and control, Active disturbance rejection control, Underwater target recognition.
2006/09-2010/07, School of electrical engineering, Tianjin University of Technology, China, B.S. in Automation;
2010/09-2013/03, School of electrical engineering, Tianjin University of Technology, China, M.S. in Control theory and control engineering;
2013/09-2016/07, School of computer and control engineering, Nankai University, China, Ph.D. in Control science and Engineering;
2016/09-2019/06, Intelligent manufacturing college, Nankai University, China, Ph.D. in Control science and Engineering;
2019/0- College of artificial intelligence, Nankai University, post-doctoral.
[1] National Natural Science Foundation of China (Youth program), 62103204, Research on agile trajectory tracking and disturbance rejection optimization control of parawing unmanned aerial vehicle, 2022.01-2024.12, under research, PI.
[2] National Natural Science Foundation of China (General Program), 62073177, Optimization and analysis of typical control structures for hypersonic flight subject to intrinsical constraints, 2021.01-2024.12, under research, Co-PI.
[3] Awards: Intelligent ground station of parachute system, Tianjin Science and Technology Bureau, Second prize of scientific and technological progress, 2020.
[1] Tan Panlong, Sun Mingwei, Sun Qinglin, et al. Linear Stabilization Control for Underactuated RTAC Based on Model Reconstruction [J]. IEEE-ASME Transactions on Mechatronics, 2021. (DOI: 10.1109/TMECH.2021.3086959).
[2] Tan Panlong, Sun Mingwei, Sun Qinglin, et al. Dynamic Modeling and Experimental Verification of Powered Parafoil With Two Suspending Points [J], IEEE Access, 8: 12955-12966, 2020.
[3] Tan Panlong, Qin Huayang, Sun Mingwei, et al. Sliding Mode Active Disturbance Rejection Control for Underactuated RTAC [J]. Control theory and Application, 2021. (Accepted).
[4] Tan Panlong, Qin Huayang, Sun Mingwei, et al. Neural Network-Based Adaptive Sliding Mode Control Strategy for Underactuated RTAC [C], 2020 Chinese Automation Congress (CAC), Shanghai, China, 2020: 6244-6249.
[5] Qin Huayang, Tan Panlong, Chen Zengqiang, et al. Deep reinforcement learning based active disturbance rejection control for ship course control [J]. Neurocomputing. 2021. (DOI: 10.1016/j.neucom.2021.06.096).
[6] Yu Zhenping, Tan Panlong, Sun Qinglin, et al. Longitudinal wind field prediction based on DDPG [J]. Neural Computing & Applications, 2021. (Accepted).