Prescribed time reliable platooning control for connected autonomous vehicles using neural network adaptive estimator approach

This paper studied the prescribed-time platooning control problem for connected autonomous vehicles subject to unknown dynamics and stochastic actuator faults. Precisely, to compensate for the effect of unknown dynamic behaviour, the radial basis function-based adaptive observer design was developed that incorporates into the closed-loop control system, which enhances the robustness of the proposed control algorithm. In addition, physical actuator fault factors are also taken into account, which are denoted in terms of a Bernoulli-distributed stochastic variable. Lyapunov stability theory and the stochastic analysis method is used to derive the stability of the addressed control system. Finally, a numerical example with detailed simulation results is provided to illustrate the effectiveness of the proposed control design.