With the development of agricultural mechanization and information technology, automatic navigation tractors are becoming a more common piece of farm equipment. The accuracy of automatic navigation tractor path tracking has become critical for maximizing efficiency and crop yield. Aiming at improving path tracking control accuracy and the real-time performance of the traditional model predictive control (MPC) algorithm, the study proposed an adaptive time-domain parameter with MPC in the path tracking control of the articulated steering tractor. Firstly, the kinematics model of the articulated steering tractor was established, as well as the multi-body dynamics model by RecurDyn. Secondly, the genetic algorithm was combined with MPC. The genetic algorithm was used to calculate the optimal time domain parameters under real-time vehicle speed, vehicle posture and road conditions, and the adaptive MPC was realized. Then, path tracking simulations were conducted by combining RecurDyn and Simulink under different path types. Compared with the traditional MPC algorithm under the three paths of U-shaped, figure-eight-shaped and complex curves, the maximum lateral deviations of the modified MPC algorithm were reduced by 59.0%, 24.9% and 13.2%, respectively. At the same time, the average lateral deviation was reduced by 72%, 43.5% and 20.3%, respectively. Finally, the real path tracking tests of the articulated steering tractor were performed. The test results indicated that under the three path tracking conditions of straight line, front wheel steering and articulated steering, the maximum lateral deviation of the modified MPC algorithm was reduced by 67.8%, 44.7% and 45.1% compared with the traditional MPC. The simulation analysis and real tractor tests verified the proposed MPC algorithm, considering the adaptive time-domain parameter has a smaller deviation and can quickly eliminate the deviation and maintain tracking stability.

With the development in agricultural mechanization and information technology, orchard agricultural machinery is also constantly pursuing the goal of intelligence and efficiency. Fruit picking is the most labor-intensive part of the orchard harvesting process. In order to resolve the problems of high labor intensity, low picking efficiency, and labor shortage when harvesting dwarf high-density orchards, an automatic navigation fruit-picking platform with voice control was developed in the present study. First, the platform utilized a voice-controlled high-level extendable working platform and a fruit-box-lifting device to adapt to varying orchard planting row spacing and enable convenient fruit box loading and unloading. Second, an automatic navigation system, which employed China’s Beidou navigation satellite system to acquire positional data and the Stanley algorithm for path-tracking control, was implemented. Third, the fruit-picking platform with automatic navigation system was fabricated and assembled, its outer wheel steering was measured to have a maximum angle of 30.3° and an average minimum turning radius of 4.5 m, meeting the turning radius requirements under orchard conditions. Finally, automatic navigation tests of the developed platform were performed in the orchard conditions. The results indicated that the platform could maintain a straight-line path with a maximum lateral deviation of 101.5 mm and a maximum absolute average deviation of 44.1 mm at 0.4 m/s. Under the U-shaped paths, the measured maximum lateral deviation was 148.6 mm and the maximum absolute average deviation was 57.2 mm. The navigation accuracy was sufficient to meet the requirements for the harvesting platform’s routine operation in the orchards.

With the benefits of small turning radius and high trafficability, the articulated steering half-track tractor had been widely utilized in orchard and small spaced farmland. To study the dynamic performance of the articulated steering half-track tractor and provide a model basis for studying the path tracking control, an accurate multi-body dynamic model of the tractor was required. In this study, the crucial parameters in the dynamic model construction of the tractor were investigated. Firstly, the topology model of the components of the half-track tractor was built by RecurDyn, in which the movement subs and driver functions were given. Secondly, considering the difference of dynamic characteristic of the articulated steering tractor with respect to different pavement hardnesses, the soft and hard pavement models were constructed by employing the harmonic superposition method. Finally, the simulations of the half-track tractor under straight-line and swerve had been conducted on the two types of pavements, and the simulation results were compared with the experimental and theoretical results. The results indicated that the average speed error of the dynamic model on hard pavement and farmland soft pavement were 2.7% and 2.1% compared with the real tractor tests. At the same time, the straight-line driving offset errors of the dynamic model on the two pavements were 1.6% and 3.8% for the front wheels and the rear wheels offset errors were 3.9% and 2.4%, respectively. Furthermore, the turning radius error under front wheel steering was 8.2% and the error under articulated steering was 5.3%. It is proved that the established dynamic model had high accuracy, which provides an efficient approach to analyze the dynamic features of the half-track tractor. Keywords: articulated steering, half-track tractor, multi-body dynamics, model verification, real tractor test DOI: 10.25165/j.ijabe.20231606.8165 Citation: Zhou B C, Chen S Y, Hu J N, You Y, Wang D C, Zhang Q. Multi-body dynamics modeling and test of an articulated steering half-track tractor. Int J Agric & Biol Eng, 2023; 16(6): 124–133.

Method for the posture control of bionic mechanical wheel-legged vehicles in hilly and mountainous areas

The dry sliding wear behavior of the Al-12Si-CuNiMg matrix alloy and its composite reinforced with Al₂O₃ fibers was investigated using a pin-on-disk wear-testing machine. The volume fraction of Al₂O₃ fibers in the composite was 17 vol.%. Wear tests are conducted under normal loads of 2.5, 5.0, and 7.5 N, and sliding velocities of 0.25, 0.50, and 1.0 m/s. Furthermore, the worn surfaces of the matrix alloy and the composite were examined using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The results showed that the wear resistance of the composite was inferior to that of the matrix alloy, which could be attributed to the high content of reinforcement and casting porosities in the composite. Worn-surface analysis indicates that the dominant wear mechanisms of both materials were abrasive wear and adhesive wear under the present testing conditions.