中文
HU Wei
Basic information Education Professional Experience Research Field Projects Teaching Courses Paper Monograph Patent Awards and honors Social Appointments
Personal Profile

Basic information

Name：

HU Wei

Administrative Post：

Technical Post：

Associate Professor

Degree：

Ph.D

Mailing Address：

School of Traffic and Transportation,No.3 Shangyuancun, Haidian District, Beijing 100044 P. R. China

Postcode：

100044

Office Phone：

Email：

huwei@bjtu.edu.cn

Education

Dr. HU Wei  received his M.S. degree at the Department of Mathematics, Beijing Jiaotong University, China in 2016, and Ph.D. degree in CRIStAL, UMR CNRS 9189, Centrale Lille, France in 2019. 

Professional Experience

12.2019--Now  Associate Professor  School of Traffic and Transportation, Beijing Jiaotong University

Research Field

Cooperative control of multiple vehicle/agent systems; Parameter identification of nonlinear systems; Nonlinear dynamics and control; Evolutionary algorithms and their applications. 

Projects

01/04/2020-31/03/2023 Modeling, control and optimization of connected and autonomous vehicle platoon under complex environments, the Fundamental Research Funds for the Central Universities , Grant 2020RC103, PI

Teaching Courses

Undergraduate: Traffic data analysis method

Paper
  1. Cui, Y., Hu, W.*, & Rahmani, A. (2022). A reinforcement learning based artificial bee colony algorithm with application in robot path planning. Expert Systems with Applications, 203, 117389.（SCI）
  2. Wang, S., Hu, W., Riego, I., & Yu, Y. (2022). Improved surrogate-assisted whale optimization algorithm for fractional chaotic systems' parameters identification. Engineering Applications of Artificial Intelligence, 110, 104685.（SCI）
  3. Cui, Y., Hu, W.*, & Rahmani, A. (2022). Improved artificial bee colony algorithm with dynamic population composition for optimization problems. Nonlinear Dynamics, 107(1), 743-760.（SCI）
  4. Hu, W., Yu, Y., Rahmani, A., & Wen, G. (2021). Robust consensus tracking based on hABC algorithm with parameters identification for uncertain nonlinear FOMASs with external disturbances. Journal of the Franklin Institute, 358(18), 9975-10003.（SCI）
  5. Wang, S., Yu, Y., & Hu, W.* (2021). Static and dynamic solar photovoltaic models' parameters estimation using hybrid Rao optimization algorithm. Journal of Cleaner Production, 315, 128080. （SCI）
  6. Hu, W., Wen, G., Rahmani, A., Bai, J., & Yu, Y. (2020). Leader‐following consensus of heterogenous fractional‐order multi‐agent systems under input delays. Asian Journal of Control , 22(6), 2217-2228.（SCI）
  7. Zhang, Y., Wen, G., Rahmani, A., Peng, Z., & Hu, W. (2020). Cluster consensus of multi-agent systems with general linear and nonlinear dynamics via intermittent adaptive pinning control. Transactions of the Institute of Measurement and Control, 0142331220975254.（SCI）
  8. Hu, W., Wen, G., Rahmani, A., & Yu, Y. (2019). Parameters estimation using mABC algorithm applied to distributed tracking control of unknown nonlinear fractional-order multi-agent systems. Communications in Nonlinear Science and Numerical Simulation, 79, 104933. （SCI）
  9. Hu, W., Wen, G., Rahmani, A., & Yu, Y. (2019). Differential evolution-based parameter estimation and synchronization of heterogeneous uncertain nonlinear delayed fractional-order multi-agent systems with unknown leader. Nonlinear Dynamics, 97(2), 1087-1105.（SCI）
  10. Hu, W., Wen, G., Rahmani, A., & Yu, Y. (2019). Distributed consensus tracking of unknown nonlinear chaotic delayed fractional-order multi-agent systems with external disturbances based on ABC algorithm. Communications in Nonlinear Science and Numerical Simulation, 71, 101-117.（SCI）
  11. Jiang, W., Peng, Z., Rahmani, A., Hu, W., & Wen, G. (2018). Distributed consensus of linear MASs with an unknown leader via a predictive extended state observer considering input delay and disturbances. Neurocomputing, 315, 465-475.（SCI）
  12. Hu, W., Yu, Y., & Gu, W. (2018). Parameter estimation of fractional-order arbitrary dimensional hyperchaotic systems via a hybrid adaptive artificial bee colony algorithm with simulated annealing algorithm. Engineering Applications of Artificial Intelligence, 68, 172-191.（SCI）
  13. Gu, W., Yu, Y., & Hu, W. (2017). Artificial bee colony algorithm-based parameter estimation of fractional-order chaotic system with time delay. IEEE/CAA Journal of Automatica Sinica, 4(1), 107-113.（EI）
  14. Cui, X., Yu, Y., Wang, H., & Hu, W. (2016). Dynamical analysis of memristor-based fractional-order neural networks with time delay. Modern Physics Letters B, 30(18), 1650271.（SCI）
  15. Gu, W., Yu, Y., & Hu, W. (2016). Parameter estimation of unknown fractional-order memristor-based chaotic systems by a hybrid artificial bee colony algorithm combined with differential evolution. Nonlinear Dynamics, 84(2), 779-795.（SCI）
  16. Hu, W., Yu, Y., & Zhang, S. (2015). A hybrid artificial bee colony algorithm for parameter identification of uncertain fractional-order chaotic systems. Nonlinear Dynamics, 82(3), 1441-1456.（SCI）
  17. Hu, W., Yu, Y., & Wang, S. (2015). Parameters estimation of uncertain fractional-order chaotic systems via a modified artificial bee colony algorithm. Entropy, 17(2), 692-709.（SCI）
  18. Zhang, S., Yu, Y., & Hu, W. (2014). Robust stability analysis of fractional-order Hopfield neural networks with parameter uncertainties. Mathematical Problems in Engineering, 2014.（SCI）

Monograph

Patent

Awards and honors

11/2020 Second Prize of Teaching Fundamental Skills Competition,  School of Traffic and Transportation
03/2016 Outstanding Graduate  in Beijing
03/2016 Outstanding Student in Beijing
11/2015 National Scholarship for Graduate Students, BJTU
01/2015 The Third Prize of Outstanding Learning Scholarship, BJTU
11/2014 Outstanding Graduate Student Leader, BJTU
12/2013 The Third Prize of the 10th Night of English Culture, BJTU
09/2013 The Third Prize of Outstanding Learning Scholarship, BJTU

Social Appointments