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作者:

Hua, Zhen (Hua, Zhen.) | Zhan, Jingyuan (Zhan, Jingyuan.) | Zhang, Liguo (Zhang, Liguo.)

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EI Scopus

摘要:

In the control problem of a mixed vehicle platoon including connected autonomous vehicles (CAVs) and human-driven vehicles (HDVs) in an arbitrary sequence, the behaviors of HDVs can not be described and predicted by accurate models because of disturbances and modeling errors. Considering the uncertainties of HDVs, a decentralized tube model predictive control (MPC) algorithm based on the feedback control and feedforward control is proposed for CAVs in the mixed vehicle platoon. Firstly, we construct a generic nominal system model and an actual system model for each sub-platoon based on the linearized kinematics of HDVs and CAVs. Secondly, the tube invariant set sequence centered on the nominal system trajectories is constructed with the feedforward control, and then the actual trajectories of all vehicles in each sub-platoon are restricted in the tube with the feedback control. Finally, numerical simulations are given to verify that the proposed tube MPC algorithm can overcome the uncertainties of HDVs to achieve formation control of the mixed vehicle platoon. © 2022 Technical Committee on Control Theory, Chinese Association of Automation.

关键词:

Uncertainty analysis Vehicles Feedback control Feedforward control Predictive control systems Model predictive control Tubes (components)

作者机构:

  • [ 1 ] [Hua, Zhen]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
  • [ 2 ] [Hua, Zhen]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 3 ] [Zhan, Jingyuan]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
  • [ 4 ] [Zhan, Jingyuan]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 5 ] [Zhang, Liguo]Beijing University of Technology, Faculty of Information Technology, Beijing; 100124, China
  • [ 6 ] [Zhang, Liguo]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China

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ISSN: 1934-1768

年份: 2022

卷: 2022-July

页码: 5429-5434

语种: 英文

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