Platoon Control of Unmanned Tracked Vehicles Based on Distributed Model Prediction

Derun Li, Shaobin Wu, Jiaxing Lu, Zheng Zang, Zhiwei Li, Zeyue Tang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Considering that the current platoon control algorithms applied in unmanned tracked vehicles have poor reliability and stability. There are also few research employing the model predictive control in this field of the tracked vehicles. To accomplish the platoon control of unmanned tracked vehicles, this paper proposed a Distributed Model Predictive Control (DMPC) method for platoon control. Firstly, a platoon control framework of tracked vehicles is constructed including vehicles interaction layer and vehicle nodes layer. We build a communication network topology model based on graph theory in the interaction layer and a instantaneous steering center tracked vehicle model in the node layer. Secondly, a tracked vehicle multi-objective optimization controller based DMPC is designed. The controller solves the trajectory tracking and platoon control problems uniformly. The effectiveness, stability and reliability of the controller are verified by the straight-line changeable speed platoon control experiment and circular path platoon control experiment.

Original languageEnglish
Title of host publicationProceeding - 2021 China Automation Congress, CAC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3549-3554
Number of pages6
ISBN (Electronic)9781665426473
DOIs
Publication statusPublished - 2021
Event2021 China Automation Congress, CAC 2021 - Beijing, China
Duration: 22 Oct 202124 Oct 2021

Publication series

NameProceeding - 2021 China Automation Congress, CAC 2021

Conference

Conference2021 China Automation Congress, CAC 2021
Country/TerritoryChina
CityBeijing
Period22/10/2124/10/21

Keywords

  • distributed model prediction
  • platoon control
  • unmanned tracked vehicle

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