Constraint‐Driven Multilane Merging Control for Underactuated Connected and Automated Vehicle System With Mismatched Uncertainty
ABSTRACT This article investigates the merging control for underactuated connected and automated vehicle (CAV) systems with mismatched uncertainty. The objective is to guarantee the safe and prescribed dynamic performance of the system during multilane merging. For CAV multidimensional motions, a strongly coupled vehicle dynamics with time‐varying uncertainties is constructed. For the nominal system, the control objectives are designed as system constraints, with equality constraints guaranteeing merging and time‐varying inequality constraints guaranteeing dynamic performance bounds. Based on the diffeomorphism method and bounded constraint, the system constraints are reconstructed to a unified representation. Combining system constraints and underactuated structure, the nominal controller is derived based on constraint‐following. For the uncertain system, the uncertainty is decomposed into matched and mismatched portions by orthogonal decomposition. The adaptive robust controller is designed based only on matched uncertainty. Through Lyapunov minimax analysis, the control renders the errors uniformly bounded and uniformly ultimately bounded. Simulation results show that merging and platooning are effectively achieved with the proposed control. The system has excellent transient and steady state performance even in the presence of time‐varying uncertainties.
Authors
- Jiawen Li (ORCID: https://orcid.org/0009-0002-3910-1776)
- Xueyun Li (ORCID: https://orcid.org/0000-0001-8439-6871)
- Linjie Ren (ORCID: https://orcid.org/0000-0002-3821-3285)
- Jin Huang (ORCID: https://orcid.org/0000-0002-1803-7077)
- Qinwen Yang (ORCID: https://orcid.org/0000-0002-0379-8404)
- Gang Xiao (ORCID: https://orcid.org/0000-0003-1003-8945)
Institutions
- Hunan University (CN)
- Wuhan University of Technology (CN)
- Jiangxi Copper (China) (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- International Journal of Robust and Nonlinear Control
- Published
- 2024-11-06
- DOI
- https://doi.org/10.1002/rnc.7700
- Primary Topic
- Traffic control and management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Jiangxi Province
- Guangxi University
- National Key Research and Development Program of China