Adaptive Backstepping Fuzzy Lateral Motion Control Approach for Autonomous Vehicles

Vehicle lateral motion control is a critical technology for fully automated driving. However, the nonlinearity of the vehicle and the uncertainty of state parameters present significant challenges for precise motion control. To address these problems, the adaptive backstepping fuzzy control (ABFC) approach for autonomous vehicles’ lateral motion is proposed. The steering system model and the vehicle dynamics model are combined into a strict feedback model to represent the response of the vehicle under steering system inputs. The ABFC strategy is designed using the fuzzy logic system (FLS) to approximate nonlinear and unknown parameters in the model, improving the control accuracy. The parameter update law estimates the boundary of the unknown disturbances, which ensures the stability of the system. In addition, a robust term is added to the parameter update law to enhance the convergence rate of the parameters. Finally, simulations and experiments are conducted, and the results show that the ABFC strategy has excellent tracking performance and stability under parameter uncertainty and nonlinearity.