To improve the path tracking accuracy of autonomous tractors in operation, an improved Stanley controller (IMP-ST) is proposed in this paper. The controller was applied to a two-wheel tractor dynamics model. The parameters of the IMP-ST were optimized by multiple-population genetic algorithm (MPGA) to obtain better tracking performance. The main purpose of this paper is to implement path tracking control on an autonomous tractor. Thus, it is significant to study this field because of smart agricultural development. According to the turning strategy of tractors in field operations, five working routes for tractors were designed, including straight, U, Ω, acute-angle and obtuse-angle routes. Simulation tests were conducted to verify the effectiveness of the proposed IMP-ST in tractor path tracking for all routes. The lateral root-mean-square (RMS) error of the IMP-ST was reduced by up to 36.84% and 48.61% compared to the extended Stanley controller and the original Stanley controller, respectively. The simulation results indicate that the IMP-ST performed well in guiding the tractor to follow all planned working routes. In particular, for the U and Ω routes, the two most common turning methods in tractor field operations, the path tracking performance of the IMP-ST was improved by 41.72% and 48.61% compared to the ST, respectively. Comparing and analyzing the e-Ψ and β-γ phase plane of the three controllers, the results indicate that the IMP-ST has the best control stability.

Corn harvesting mode has gradually changed from ear harvesting to direct grain harvesting. In view of the problems of high moisture content in corn harvesting in China, such as the rates of broken grains (BGR) and uncleared grains (UGR) being too high, a new single longitudinal axial threshing cylinder was designed, which mainly included a cylinder spindle, a spiral feeding inlet, a T-type rasp bar, a separating straight rod, and a spiral extracting rod. Firstly, the three states of grain during the threshing process and the key influence factors of threshing and force analysis of corn ears in the threshing device were analyzed, then the structure of the threshing cylinder was designed, and its parameters were determined by theoretical analysis results. The arrangement mode of threshing elements adopted a combination of a T-type rasp bar, a separating straight rod, and a spiral extracting rod with a 6-head spiral pattern and an arrangement step of 250 mm. Secondly, the arrangement step of threshing elements was determined by discrete element method solution (DEM) simulation; the result showed that the average movement velocity was 55.04 m/s and the threshing time was 6–8 s. Finally, a multiple factors experiment of the threshing device was carried out, and the result showed that the order of the effect factors of the BGR and UGR was cylinder rotational speed > concave clearance > feed amount. When cylinder rotational speed was 309.17 r/min, concave clearance was 35.48 mm, and the feed amount was 6.13 kg/s. The verification experiment result showed that the BGR and UGR were 1.24% and 1.33%, respectively, which meet standard requirements. The research results could provide a reference for the design of a high moisture content grain threshing device and combine harvester.

In a tractor automatic navigation system, path planning plays a significant role in improving operation efficiency. This study aims to create a suboptimal reference course for headland turning of a robot tractor and design a path-tracking controller to guide the robot tractor along the reference course. A time-minimum suboptimal control method was used to generate the reference turning course based on the mechanical parameters of the test tractor. A path-tracking controller consisting of both feedforward and feedback component elements was also proposed. The feedforward component was directly determined by the desired steering angle of the current navigation point on the reference course, whereas the feedback component was derived from the designed optimal controller. Computer simulation and field tests were performed to validate the path-tracking performance. Field test results indicated that the robot tractor followed the reference courses precisely on flat meadow, with average and standard lateral deviations being 0.031 m and 0.086 m, respectively. However, the tracking error increased while operating on sloping meadow due to the employed vehicle kinematic model.

The rapid development of peanut mechanization has increased the amount of dust expelled from peanut mechanized operations, which degrades the air quality and endangers the health of agricultural workers. Therefore, the purpose of this study is to figure out the characteristics of dust emission from mechanized peanut harvesting. To this end, the particulate matters of diameters ≤ 2.5 μm and ≤10 μm and the total suspended particles were sampled in real time during peanut harvesting in Henan Province, China, and the airborne particle concentrations and particle size distributions were measured. The dust particles discharged during the mechanized peanut harvesting were concentrated within the 2~30 µm size range. When the wind speed was reduced below the settling velocity of the largest particles, the more massive particles were carried in the downwind. The amount of free silica in the dust samples was determined by X-ray diffraction analysis. Both the total dust and free silica concentrations exceeded the occupational exposure and threshold limits. To improve the characteristics of dust emission, the microstructure and dispersion of the dust were also investigated. Reducing the agricultural operations during periods of high wind speed, low crop-moisture content, and low air humidity is recommended for reducing the dust exposure of workers. The results will provide guidance and technical support for reducing the dust emissions of mechanized harvesting operations, improving air quality, and reducing the health hazards to operators.

In order to realize the pressure control of the tractor electronic hydraulic hitch in the fields, the pressure control algorithm is essential. In this study, combining the kinematics model with the dynamic model of ploughing and the hydraulic system model, an adaptive fuzzy PID controller is proposed to adjust the real-time data of the PID parameters for the pressure control of the tractor electronic hydraulic hitch. The feasibility of the proposed controller was verified by simulation. Next, a pressure control experimental with the real vehicle experiment platform was carried out under three control algorithms of the traditional PID, the traditional PID with compensation correction and the adaptive fuzzy PID with compensation correction in verifying the pressure control effect of the tractor in different controllers. When the system was stable, the experimental results showed that the input was 1.5 MPa step signal with response time in the traditional PID controller of 2.5 s, fluctuation range of 0.5 MPa. However, the response time in the adaptive fuzzy PID with compensation correction was 1.5 s, fluctuation range of 0.3 MPa. The responding time was 40% lower, and the pressure fluctuation range was reduced by 40%. In conclusion, the proposed algorithm successfully realized the pressure control of the tractor. The proposed adaptive fuzzy PID with compensation correction in this paper has a better dynamic performance.