Trajectory tracking control for intelligent driving vehicles based on double integral sliding mode and disturbance observer

Abstract When intelligent driving vehicles drive in unknown environments, they are susceptible to external disturbances, which can reduce trajectory tracking accuracy and driving stability. To address this issue, this paper proposes a fractional-order double-integral sliding mode control (SMC) strategy based on barrier function (BF) reaching law and nonlinear disturbance observer (NDOB). First, a NDOB is used to estimate and compensate for lumped disturbances in real-time, enhancing the system’s disturbance rejection capability. Next, a double-integral sliding surface combining fractional-order and integer-order integrals is designed to improve the system’s flexibility and stability. To effectively suppress chattering caused by excessively large reaching law control gains, a BF is introduced to dynamically adjust the control gain, ensuring stable system operation. Finally, joint simulations using Carsim-Simulink are conducted to validate the superiority of the proposed control strategy in various lane change scenarios. Compared to traditional SMC (TSMC) and super twisting SMC methods, trajectory tracking accuracy is improved by 51.4% to 81.25%, demonstrating significant adaptability and superior control performance.