Asynchronous self-triggered stochastic distributed MPC for cooperative vehicle platooning over vehicular ad-hoc networks

In this paper, an asynchronous stochastic self-triggered distributed MPC (DMPC) control scheme is proposed for vehicular platoon systems under coupled state constraints and additive stochastic disturbance. In considered platoon systems, each vehicle broadcasts its predicted state as beacon informati...

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المؤلفون الرئيسيون: Chen, Jicheng, Wei, Henglai, Zhang, Hui, Shi, Yang
مؤلفون آخرون: School of Mechanical and Aerospace Engineering
التنسيق: مقال
اللغة:English
منشور في: 2023
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الوصول للمادة أونلاين:https://hdl.handle.net/10356/171820
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المؤسسة: Nanyang Technological University
اللغة: English
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spelling sg-ntu-dr.10356-1718202023-11-09T01:58:58Z Asynchronous self-triggered stochastic distributed MPC for cooperative vehicle platooning over vehicular ad-hoc networks Chen, Jicheng Wei, Henglai Zhang, Hui Shi, Yang School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Model Predictive Control Platoon Systems In this paper, an asynchronous stochastic self-triggered distributed MPC (DMPC) control scheme is proposed for vehicular platoon systems under coupled state constraints and additive stochastic disturbance. In considered platoon systems, each vehicle broadcasts its predicted state as beacon information to its neighbouring vehicles through the vehicular ad-hoc network (VANET). To reduce the communication burden in the VANET, each vehicle proactively determines the next sampling time instant by solving the stochastic self-triggered DMPC problem at the sampling time instant. The self-triggered problem is formulated by utilizing local vehicle states and asynchronous beacon information from its neighbours. Consequently, the proposed scheme reduces the communication load dramatically in the VANET while maintaining a satisfactory control performance compared to periodic time-triggered stochastic DMPC. To handle the state coupling between vehicles, e.g., for collision avoidance or communication connectivity purpose, probabilistic coupled state constraints are incorporated into the DMPC problem. Based on the information on stochastic disturbance, the probabilistic coupled state constraints are transformed into deterministic forms using the stochastic tube-based method. Theoretical analysis has shown that closed-loop platooning is quadratically stable at triggering time instants. Numerical examples illustrate the efficacy of the proposed control method in terms of data transmission reduction. This work was supported by the Defense Industrial Technology Development Program. 2023-11-09T01:58:58Z 2023-11-09T01:58:58Z 2023 Journal Article Chen, J., Wei, H., Zhang, H. & Shi, Y. (2023). Asynchronous self-triggered stochastic distributed MPC for cooperative vehicle platooning over vehicular ad-hoc networks. IEEE Transactions On Vehicular Technology. https://dx.doi.org/10.1109/TVT.2023.3288210 0018-9545 https://hdl.handle.net/10356/171820 10.1109/TVT.2023.3288210 2-s2.0-85163779147 en IEEE Transactions on Vehicular Technology © 2023 IEEE. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
Model Predictive Control
Platoon Systems
spellingShingle Engineering::Mechanical engineering
Model Predictive Control
Platoon Systems
Chen, Jicheng
Wei, Henglai
Zhang, Hui
Shi, Yang
Asynchronous self-triggered stochastic distributed MPC for cooperative vehicle platooning over vehicular ad-hoc networks
description In this paper, an asynchronous stochastic self-triggered distributed MPC (DMPC) control scheme is proposed for vehicular platoon systems under coupled state constraints and additive stochastic disturbance. In considered platoon systems, each vehicle broadcasts its predicted state as beacon information to its neighbouring vehicles through the vehicular ad-hoc network (VANET). To reduce the communication burden in the VANET, each vehicle proactively determines the next sampling time instant by solving the stochastic self-triggered DMPC problem at the sampling time instant. The self-triggered problem is formulated by utilizing local vehicle states and asynchronous beacon information from its neighbours. Consequently, the proposed scheme reduces the communication load dramatically in the VANET while maintaining a satisfactory control performance compared to periodic time-triggered stochastic DMPC. To handle the state coupling between vehicles, e.g., for collision avoidance or communication connectivity purpose, probabilistic coupled state constraints are incorporated into the DMPC problem. Based on the information on stochastic disturbance, the probabilistic coupled state constraints are transformed into deterministic forms using the stochastic tube-based method. Theoretical analysis has shown that closed-loop platooning is quadratically stable at triggering time instants. Numerical examples illustrate the efficacy of the proposed control method in terms of data transmission reduction.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Chen, Jicheng
Wei, Henglai
Zhang, Hui
Shi, Yang
format Article
author Chen, Jicheng
Wei, Henglai
Zhang, Hui
Shi, Yang
author_sort Chen, Jicheng
title Asynchronous self-triggered stochastic distributed MPC for cooperative vehicle platooning over vehicular ad-hoc networks
title_short Asynchronous self-triggered stochastic distributed MPC for cooperative vehicle platooning over vehicular ad-hoc networks
title_full Asynchronous self-triggered stochastic distributed MPC for cooperative vehicle platooning over vehicular ad-hoc networks
title_fullStr Asynchronous self-triggered stochastic distributed MPC for cooperative vehicle platooning over vehicular ad-hoc networks
title_full_unstemmed Asynchronous self-triggered stochastic distributed MPC for cooperative vehicle platooning over vehicular ad-hoc networks
title_sort asynchronous self-triggered stochastic distributed mpc for cooperative vehicle platooning over vehicular ad-hoc networks
publishDate 2023
url https://hdl.handle.net/10356/171820
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