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.

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.

Most automatic steering systems for large tractors are designed with hydraulic systems that run on either constant flow or constant pressure. Such designs

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.

According to the characteristics of the ant colony optimization and the K-means clustering, a method for the image segmentation based on the ant colony optimization and the K-means clustering was proposed in this paper. Firstly, the basic principle of the two algorithms were introduced. Secondly, their characteristics on the image segmentation were analyzed. Finally the improved algorithm was proposed, this algorithm can effectively overcome shortages which are the slow rate of the ant colony optimization and the K-means clustering dependent on the initial clustering centers. Experimental results proved that the improved algorithm was an effective method for the image segmentation in the practical application, which could segment the object accurately.

In view of the problems of poor working quality and low efficiency caused by traditional hitch mechanisms, which cannot make farm implements adapt to hillside fields for terrain-adaptive working after leveling the body of hilly tractors, a new type of terrain-adaptive hitch mechanism was designed which can adjust the transverse posture of farm implements to meet the ploughing requirements of complicated terrain in hilly and mountainous areas. The mechanism was mainly composed of the original hitch device and the newly added rotating device. The kinematic model of each sub-mechanism was established, as well as the mathematical relation of significant performance indexes of the whole mechanism, such as lifting capacity, transverse inclination angle and tillage depth. Genetic algorithm was used to optimize the lifting performance of this hitch mechanism in Matlab, so that the minimum vertical lifting force at the center of gravity of farm implements increased by 14.1%, which met the requirements of national standards. Through ADAMS simulation calculation, it was found that different working slopes had a certain influence on the external load of each component, and terrain-adaptive hitch mechanism had little effect on the vibration characteristics of hilly tractors. The fatigue analysis and optimization design of the key component, rotating shaft, were carried out in ANSYS Workbench, and the mass of this part reduced by 64%. A real vehicle test platform was set up to test and verify the power lifting range and working slope range of terrain-adaptive hitch mechanism. The test results showed that the actual power lifting ranged in 185-857 mm, and the maximum error from the theoretical range was only 3.1%, while the actual working slope range was from –25.9° to +23.2°, and the maximum error from the theoretical range was only 4.5%. Therefore, the terrain-adaptive hitch mechanism can meet the requirements of power lifting performance, and simultaneously can adjust the transverse posture of farm implements for adapting to hillside fields of no less than 20°. Keywords: hilly tractors, hitch mechanism, terrain-adaptive working, transverse posture, optimal design DOI: 10.25165/j.ijabe.20231604.6992 Citation: Xin Z, Jiang Q B, Zhu Z X, Shao M X. Design and optimization of a new terrain-adaptive hitch mechanism for hilly tractors. Int J Agric & Biol Eng, 2023; 16(4): 134–144.