Research on FSAC trajectory tracking control based on optimized BP neural network algorithm

A longitudinal linear quadratic regulation LQR acceleration motion controller and a lateral linear model prediction (LTV-MPC) motion controller are designed to address the accuracy and stability of trajectory tracking with a four-wheel independent drive driverless formula car. Based on the BP neural network algorithm, the prediction step and control step parameters of the model prediction control are adaptively adjusted, and the genetic optimisation algorithm is used to optimise the BP neural network to improve the lateral trajectory tracking accuracy of the car. The simulation results show that the proposed lateral motion control strategy can control the unmanned racing car to track the lateral trajectory well during the trajectory tracking process.