In this paper, the path-tracking control strategies are proposed for autonomous agricultural vehicles with unknown matched-mismatched disturbances. First of all, a second-order disturbance observer (DOB) is designed to estimate the matched and mismatched disturbances to mitigate their negative effects. Secondly, by introducing a modified sliding mode surface, a DOB-based first-order sliding mode (FOSM) control scheme is proposed to effectively deal with the system lumped disturbance. To completely eliminate the chattering problem existing in the designed DOB-based FOSM controller, a DOB-based barrier function adaptive sliding mode (BFASM) control strategy is further proposed. The distinguishing feature of the developed BFASM control strategy is that the designed sliding variable can be finite-time stabilized to a predefined neighborhood around the origin, and the upper bound of lumped disturbance does not require to be known in advance. The practical stability of the overall path-tracking system is demonstrated by using the rigorous Lyapunov theory analysis. Finally, some comparative simulations and experiments are conducted to highlight the strong robustness, adaptability, and excellent tracking performance of the developed barrier function-based adaptive path-tracking control strategy.

In order to solve the labor shortage problem, unmanned agricultural vehicles have been widely promoted in China. Among these vehicles, unmanned tractor-trailers have garnered the most interest thanks to their flexibility and efficiency. However, trapped by the factors of vehicle parameter uncertainties, unstructured farmland roads, etc., the current unmanned tractor-trailers have shown poor tracking accuracy and longer online times in straight-line path tracking. To overcome the aforementioned issues, a fuzzy sliding mode control (FSMC) approach is proposed in this paper. First, the tractor-trailer path tracking error model was established based on the kinematic model and a reference model. Then, according to the sliding mode control (SMC) theory, the FSMC was designed. Through a Lyapunov theory analysis, the proposed control method can ensure that the articulated angle, the position error, and the heading error all converge to zero. Finally, field tests and Simulink simulations demonstrated the effectiveness and robustness of the suggested control mechanism. According to field experiments, the proposed control method can increase the trailer steady-state tracking accuracy by between 10.5 and 36.8% and the tractor steady-state tracking accuracy by between 11.1 and 50%.

Current methods to control the spraying quantity present several disadvantages, such as poor precision, a long adjustment time, and serious environmental pollution. In this paper, the flow control valve and the linear active disturbance controller (LADRC) were used to control the spraying quantity. Due to the disturbance characteristics in the spraying pipeline during the actual operation, the total disturbance was observed by a linear extended state observer (LESO). A 12 m commercial boom sprayer was used to carry out practical field operation tests after relevant intelligent transformation. The experimental results showed that the LADRC controller adopted in this paper can significantly suppress the disturbance in practical operation under three different operating speeds. Compared with the traditional proportional–integral–differential controller (PID) and an improved PID controller, the response speed of the proposed controller improved by approximately 3~5 s, and the steady-state error accuracy improved by approximately 2~9%.

This article presents a modified supertwisting sliding mode (STSM) approach for path tracking control of unmanned agricultural tractors in unstructured environments. To address the challenges posed by external disturbances or uncertainties in model parameters, a disturbance observer is employed to estimate the lumped disturbance on the sliding mode (SM) dynamics. Furthermore, a nonsmooth term is introduced to replace the discontinuous signum function used in traditional STSM. By incorporating disturbance feedforward compensation and nonsmooth feedback, a modified composite nonsmooth STSM is established for effective path tracking control. The proposed modification not only eliminates the chattering problem, but also enhances the performance of the conventional STSM. The practical finite-time stability of the SM variable is rigorously verified using the Lyapunov theory. A detailed vehicle model is constructed using the Simulink/Carsim cosimulation method to ensure high accuracy and completeness. Hardware-in-loop tests are conducted to confirm the superiority of the proposed control approach.