Data-Driven Fault-Tolerant Platooning Control Under Aperiodic DoS Attacks

This paper investigates the resilient fault-tolerant model-free adaptive platooning security control (FT-MFAPSC) issue for the vehicular platooning systems (VPSs) subject to sensor faults and aperiodic denial-of-service (DoS) attacks. Firstly, an equivalent linear data model can be obtained from the nonlinear VPSs based on the partial form dynamic linearization (PFDL) technique. Then, the fault-tolerant control framework is developed with consideration of the sensor faults. The gradient descent method-based neural network is adopted in the control framework for the fault approximation. Thirdly, an attack compensation mechanism is designed for the PFDL-based controller. Aiming at the VPSs against aperiodic DoS attacks, a novel resilient FT-MFAPSC algorithm with the compensation mechanism is proposed. And the control objectives of the VPSs can be accomplished. Finally, by the simulation example with comparisons, the effectiveness of the developed algorithm can be illustrated.

Automated summary

This paper investigates the resilient fault-tolerant model-free adaptive platooning security control issue for the vehicular platooning systems subject to sensor faults and aperiodic denial-of-service attacks. Firstly, an equivalent linear data model is obtained using the partial form dynamic linearization technique. Then, a fault-tolerant control framework is developed with consideration of the sensor faults and a gradient descent method-based neural network is adopted for fault approximation. Thirdly, an attack compensation mechanism is designed and a novel resilient FT-MFAPSC algorithm is proposed for the VPSs against aperiodic DoS attacks, accomplishing the control objectives. Finally, the effectiveness of the developed algorithm is illustrated through simulation examples and comparisons.