Event-Triggered NN Dynamic Surface Consistency Tracking Control of Dual-Motor Steer-by-Wire Vehicles Under CAN Network Communication

The dual-motor steer-by-wire (DMSBW) system significantly enhances the reliability of vehicle steering systems due to its high redundancy. However, in practical steering control, the limited bandwidth of the in-vehicle controller area network (CAN) communication network often leads to issues such as packet loss and congestion. These issues can cause asynchronous time delays (ATDs) in the control signals transmitted to the dual motors, resulting in inconsistent motor angles, which severely affects the tracking accuracy of the vehicle. To address the problem, this article proposes an event-triggered neural network (NN) dynamic surface consistency tracking control strategy for DMSBW systems. First, a nonlinear model of the DMSBW system with ATD is established, with the system’s nonlinearities approximated using NNs. Then, an event-triggered dynamic surface consistency controller is designed, incorporating an auxiliary variable and event-triggering mechanism within the backstepping control framework to mitigate the effects of ATD and limited bandwidth. Additionally, the use of dynamic surface and error compensation techniques reduces the computational burden and accuracy degradation caused by the iterative derivation in backstepping control. The introduction of the dual-motor consistency errors and finite-time terms ensures fast convergence and tracking consistency of the system. Finally, hardware-in-the-loop experiments demonstrate that the proposed control strategy improves the DMSBW consistency by 45% and reduces communication load by 53.7%, effectively ensuring consistency tracking accuracy under ATD while alleviating communication burdens.