## 6 Conclusions and Outlook  
In this paper, we proposed an adaptive algorithm based on fuzzy PID controls for coupled feeding volume-traveling speed systems in rice harvesters in southern China. It is suitable for rice harvesting needs in southern China, where harvesting areas are scattered across hilly and mountainous areas. The harvester's speed could be adjusted instantly according to changes in rice feeding volume during the operation, which it subsequently optimized. Our experimental analysis showed that the harvester's adaptive traveling speed algorithm based on fuzzy PID controls was better than the traditional PID control method in many control indexes. Our field test analysis showed that a harvester regulated by the algorithm could adapt to changing field operation conditions more quickly and stabilized the feeding volume in a reasonable range to meet the needs of practical applications. Our study can provide rice harvesters with a reference for designing threshing and loss reduction equipment in southern China.  
The harsh operating environment in the field challenged the sensor's stability, and the feeding volume detection error was significant. In the future, we must continue researching methods to improve the stability of sensor detection, adjust the acquisition circuit's filtering effect, optimize data analysis and processing methods, and improve detection accuracy.  
The system is suitable for modifying small- and medium-sized combine harvesters in hilly mountainous areas. Considering the lighter mass of the small- and medium-sized combine harvesters, as well as the limited optimization of their structures, the noise and vibration were more severe during the driving process, causing deviances in the system detection and expanding control. In the future, system improvement should focus on reducing the influence of vibration and noise on the system.  
In order to improve the performance of rice harvesters and develop more effective and efficient control methods, a long-term task of this research project is to compare the fuzzy PID control strategies proposed in this paper with each other and with other control methods. We plan to conduct both quantitative and qualitative studies to achieve this goal. For the quantitative study, we will design experiments to compare the performance of the fuzzy PID control system with other control methods, such as sliding mode control and model predictive control. We will measure various performance metrics, including fuel consumption, harvest efficiency and crop damage, to assess the effectiveness of each control method. For the qualitative study, we will conduct surveys and interviews with farmers and operators to gather feedback on ease of use, reliability and their overall satisfaction with each control method.  
Conceptualization, L.D. and T.L.; methodology, T.L.; software, L.D.; validation, L.D. and J.Z.; formal analysis, L.D. and W.Y.; investigation, L.D. and A.Q.; resources, T.L., P.J. and F.X.; data curation, L.D. and J.Z.; writing--original draft preparation, L.D.; writing--review and editing, L.D. and T.L.; visualization, L.D.; supervision, T.L. and F.X.; project administration, T.L. and P.J.; funding acquisition, T.L., P.J. and F.X. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Hunan Education Department Scientific Research Project (No. 21C0126), the Hunan Agricultural Machinery Equipment and Technological Innovation R&D Project (Xiang Cai Nong Zhi [2020] No.107) and the Hunan Agricultural Machinery Equipment and Technological Innovation R&D Project (Xiang Cai Nong Zhi [2021] No.47).  
Not applicable.  
The authors declare no conflict of interest.