## 4 Results and Discussion
The above results indicate that adaptive fuzzy control has better adaptability than the traditional control methods. The performance of the system under different test scenarios is analysed to obtain Figure 11, which shows the driving of the farming machine under two scenarios: concrete and paddy field. The results of the travelling trajectory (Figure 11) show a high degree of overlap between the actual path and the desired path, with an overall average error of less than 0.001. The bias data analysis of the results of the farming machine under path tracking was carried out and the results are shown in Figure 12.  
Figure 11: Driving trajectory of agricultural machinery in two testing scenarios. Figure 12: Path tracking deviation result. In Figure 12, when in the concrete field, the maximum deviation of the straight-line section of the control system platform is 2.75 m, and the average value of the deviation of the turning section reaches 2.05 m. The large oscillation situation is mainly manifested in the turning section, and the stability of the overall control process is better. In the paddy field deviation results, the average value of the lateral deviation in the straight section is 2.03 m, and the average value of the deviation in the turning section is basically 2.54 m. According to the operation quality standard of the agricultural machine, it can be seen that the row spacing of the operation should be \(\leq\)5 cm, and the statistics of the experimental results show that the actual path deviation points account for less than 5 per cent of the actual number, which indicates that the design system can better meet the operational requirements and the qualification rate is high. The planning results of agricultural machinery operating in paddy fields are subject to certain deviations due to factors such as soil moisture and road surface smoothness. The difference between the two operating environments of agricultural machinery is due to the special nature of paddy fields. The soil in paddy fields usually has a higher moisture content, making the ground softer and smoother. The traction of agricultural machinery tyres is affected, which affects the accuracy of steering and the stability of driving. The water level in paddy fields may change due to irrigation, rainwater accumulation, or evaporation, directly affecting the difficulty of agricultural machinery operations and their adaptability to the ground. The driving of agricultural machinery in paddy fields requires sufficient power to overcome the resistance of water and the friction of muddy soil, and its power system will inevitably affect the path tracking results. To further verify the adaptability of the fuzzy control method proposed by this research institute, obstacles were set up in farmland, which were, respectively, arranged in the first and second half of the farmland planning route. Subsequently, the adjacent method was used as a comparison algorithm to analyse the turning effect of the agricultural machinery operations, and the adjacent method [34] operated according to adjacent strips. The results are shown in Figure 7:0  
The red part in the picture represents obstacles. The results of the graph indicate that the fuzzy control method used in this study performs better than the adjacent method in terms of work area and work distance, with an average improvement of 9.5% and 8.4%. In addition, this method can effectively avoid obstacles, reduce the area of turning areas, and has strong adaptability. A farmland operation plan route can reduce sharp turns and drastic flight changes, thereby reducing the risk of collisions. However, the operation plan route of the comparative method has bends and partially dense situations. Curved operation routes may be limited by the terrain of farmland, surface obstacles, etc., which may cause the machinery to be unable to move in a straight line during operation, resulting in a high risk of collision. Frequent turns may cause the equipment to be unable to avoid ground  
Figure 7:1 Path operation control effect.