Neural Network-Based Adaptive Integral Sliding Mode Control for Bidirectional Platooning with Unknown Dynamics and Disturbances

This paper proposes a neural network-based adaptive integral sliding mode control method for bidirectional vehicle platooning under unknown dynamic parameters and matched and mismatched disturbances. The unknown nonlinear dynamics induced by disturbances and parameter uncertainties are approximated and compensated using a neural network, while the uncertain vehicle mass directly affecting the control input is estimated through an adaptive law. To improve transient performance and robustness, a modified constant time-headway policy and a chattering-suppression robust control term are further incorporated. Theoretical analysis proves that the proposed controller guarantees asymptotic spacing error stability and string stability of the overall platoon system. Numerical simulations verify the effectiveness of the proposed method under disturbances and dynamic parameter uncertainties.