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

Publication Type : Journal Article

Publisher : Springer Science and Business Media LLC

Source : Scientific Reports

Url : https://doi.org/10.1038/s41598-025-89887-0

Campus : Coimbatore

School : School of Engineering

Department : Electrical and Electronics

Year : 2025

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.

Cite this Research Publication : Balakrishnan Devanathan, Palanisamy Selvaraj, Arumugam Suyampulingam, Karuppasamy Ilango, Prescribed time reliable platooning control for connected autonomous vehicles using neural network adaptive estimator approach, Scientific Reports, Springer Science and Business Media LLC, 2025, https://doi.org/10.1038/s41598-025-89887-0

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