Analysis reveals improved tracking accuracy in autonomous agricultural vehicles, indicating efficacy of a control strategy focused on disturbance observer adjustments.
Aiming at the problem that the tracking accuracy of autonomous agricultural vehicles (AAVs) is reduced in the complex farmland environment. A fixed-time second-order terminal sliding mode control (TSMC) is proposed to obtain an accurate upper bound of settling time. Then, the cornering stiffness estimation method is employed to address the challenges caused by parameter uncertainties, and a nonlinear disturbance observer (NDO) is utilized to estimate and compensate for external disturbances. To further improve tracking accuracy, a sub-regional dynamic gain adjustment mechanism is proposed to compensate for the error caused by the disturbance observer and adaptation, thereby improving the tracking accuracy of AAVs. Finally, Carsim/Simulink is utilized to validate the effectiveness and stability of the proposed control strategy.
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Xiao et al. (2025) studied this question.
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