Multi-Objective Cooperative Control of Vehicle Platoon Based on Fuzzy MPC

To simultaneously optimize multiple performances of the cooperative adaptive cruise control (CACC) system, a fuzzy MPC control strategy is proposed to achieve multi-objective cooperative control for electric vehicle platoons. The longitudinal kinematic analysis of the vehicle platoon is conducted to establish the platoon model. Based on the analysis of system performance, safety, comfort, and following performance are selected as the system's performance indexes, and a comprehensive performance function for the MPC is constructed. Fuzzy control theory is employed to optimize the weight parameters, enabling the CACC system to adapt to different conditions. The effectiveness and reliability of the fuzzy MPC control strategy are verified through co-simulation using Carsim and Simulink.

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Publication Details

Published
2025-03-26
DOI
https://doi.org/10.1109/icit63637.2025.10965301
Citations
3
Primary Topic
Industrial Technology and Control Systems
Type
article
Field-Weighted Citation Impact
3.64
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Multi-Objective Cooperative Control of Vehicle Platoon Based on Fuzzy MPC

Yunfei Yin, Wanying Zhu, Yuanlong Wei, Zeng Shiyu et al.
3 citations
Industrial Technology and Control Systems
3.64
article

Multi-Objective Cooperative Control of Vehicle Platoon Based on Fuzzy MPC

Yunfei Yin, Wanying Zhu, Yuanlong Wei, Zeng Shiyu, Zhanguo Xu
article en
3 citations

Abstract

To simultaneously optimize multiple performances of the cooperative adaptive cruise control (CACC) system, a fuzzy MPC control strategy is proposed to achieve multi-objective cooperative control for electric vehicle platoons. The longitudinal kinematic analysis of the vehicle platoon is conducted to establish the platoon model. Based on the analysis of system performance, safety, comfort, and following performance are selected as the system's performance indexes, and a comprehensive performance function for the MPC is constructed. Fuzzy control theory is employed to optimize the weight parameters, enabling the CACC system to adapt to different conditions. The effectiveness and reliability of the fuzzy MPC control strategy are verified through co-simulation using Carsim and Simulink.

Jilin University (CN), Harbin Institute of Technology (CN)
Openalex Percentile: Top 8%
Industrial Technology and Control Systems
3.64
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