An Adaptive Longitudinal Platooning Design Based on Concurrent Learning
- Resource Type
- Periodical
- Authors
- Wen, Q.; Liu, D.; Wang, J.; Baldi, S.
- Source
- IEEE Control Systems Letters IEEE Control Syst. Lett. Control Systems Letters, IEEE. 8:303-308 2024
- Subject
- Robotics and Control Systems
Computing and Processing
Components, Circuits, Devices and Systems
Vehicle dynamics
Mechanical power transmission
Uncertainty
Stability analysis
Adaptive control
Adaptation models
Estimation
Longitudinal platooning
automated vehicles
adaptive control
concurrent learning
- Language
- ISSN
- 2475-1456
This letter proposes a new adaptive longitudinal platooning strategy in the framework of concurrent learning. Adaptive refers to vehicles facing uncertainty in powertrain parameters via on-line estimation; concurrent learning refers to using both current and past data in the estimation. The proposed platooning strategy advances existing ones since convergence to the true powertrain parameters is guaranteed without imposing persistence of excitation on the vehicle behavior: it suffices the presence of a single non-zero data sample. Meanwhile, the concurrent learning proof we give advances existing ones since it takes into account an extra unknown gain in the error dynamics.