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

基于神经网络自适应估计器方法的联网自动驾驶车辆预定时间可靠编队控制

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Abstract

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.

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