Data-Driven Prescribed Performance Platooning Control Under Aperiodic Denial-of- Service Attacks
This article studies a data-driven prescribed performance platooning control method for nonlinear connected automated vehicle systems (CAVs) under aperiodic denial-of-service (DoS) attacks. Firstly, the dynamic linearization technique is employed to transform the nonlinear CAV system into an equivalent linearized data model. Secondly, to improve the system’s transient performance, a prescribed performance transformation (PPT) scheme is proposed to transform the constrained output into the unconstrained one. In addition, an attack compensation mechanism is designed to reduce the adverse impact. Combining the PPT scheme and the attack compensation mechanism, the data-driven adaptive platooning control scheme is proposed to achieve the vehicular tracking control task. Lastly, the merits of the developed control method are illustrated by an actual simulation.
Authors
- Zhenling Wang (ORCID: https://orcid.org/0000-0001-6227-796X)
- Wei‐Wei Che (ORCID: https://orcid.org/0000-0002-1077-3598)
- Peng Zhang (ORCID: https://orcid.org/0000-0001-5558-8743)
Institutions
- Qingdao University (CN)
- State Key Laboratory of Synthetical Automation for Process Industries
- Northeastern University (CN)
Publication Details
- Journal
- Mathematics
- Published
- 2024-10-22
- DOI
- https://doi.org/10.3390/math12213313
- Citations
- 1
- Primary Topic
- Software System Performance and Reliability
- Type
- article
- Field-Weighted Citation Impact
- 0.35
Funders
- National Natural Science Foundation of China