Distributed Stochastic Model Predictive Control for Heterogeneous Vehicle Platoons Subject to Modeling Uncertainties

Zhiyang Ju, Hui Zhang*, Ying Tan

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

38 引用 (Scopus)

摘要

This article proposes a distributed stochastic model predictive control (DSMPC) algorithm for vehicle platoons in which every vehicle is subject to modeling uncertainties. When the distributions of the uncertainties are available, DSMPC enables a less conservative treatment of the uncertainties than is commonly used for distributed robust MPC. The DSMPC problem is transformed into a deterministic one by constraint tightening. Terminal costs and constraints are carefully designed so that the recursive feasibility of the DSMPC problem is achieved. Moreover, a control update policy combined with the terminal costs design ensures the asymptotic average convergence of the vehicle states. Analysis results are presented and simulation outcomes are provided to verify the effectiveness of the proposed DSMPC method for platoon systems.

源语言英语
页(从-至)25-40
页数16
期刊IEEE Intelligent Transportation Systems Magazine
14
2
DOI
出版状态已出版 - 2022
已对外发布

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