graduate student
The article presents the development of an intelligent control system for a pneumatic precision seed drill, based on a hybrid approach combining computational fluid dynamics (CFD) and machine learning methods. Numerical modeling of the air flow in the system was performed, operational parameters were optimized, and adaptive control algorithms were developed. The results show a 15–20% improvement in seeding accuracy, an 18–22% reduction in energy consumption, and enhanced system stability under varying operating conditions. The cost-benefit analysis confirms a payback period of 2–3 seasons. Future work focuses on integration with precision agriculture technologies and the development of cloud services for collaborative algorithm training.
intelligent control, pneumatic seed drill, precision seeding, computational fluid dynamics (CFD), machine learning, adaptive algorithms, energy efficiency, cost-benefit analysis.
1. Aduov M. A. et al. Teoreticheskie i laboratornye issledovaniya central'noy pnevmaticheskoy vysevayuschey sistemy dlya shirokozahvatnoy seyalki //Herald of science of S. Seifullin Kazakh agrotechnical university: Multidisciplinary, 2024. – №. 2 (121). – S. 4-22. – Tekst: neposredstvennyy.
2. Li J. et al. Review of research on improved PID control in electro-hydraulic servo system //Recent Patents on Engineering, 2024. – T. 18. – №. 1. – S. 54-68. – Tekst: neposredstvennyy.
3. López-Gómez J. A. et al. Design and comparison of two maize seeders coupled with an agricultural robot //Machines, 2024. – T. 12. – №. 12. – S. 935. – Tekst: neposredstvennyy.
4. Obichayev I. V. A Technical analysis of the functional principles of pneumatic seeding mechanisms in modern agricultural seeders //Modern American Journal of Engineering, Technology, and Innovation, 2025. – T. 1. – №. 6. – S. 71-77. – Tekst: neposredstvennyy.
5. Raj P. et al. Validation of rotating detonation combustor computational fluid dynamics simulations for predicting unsteady supersonic–subsonic flow field at the exit //Journal of Engineering for Gas Turbines and Power, 2024. – T. 146. – №. 4. – S. 041012. – Tekst: neposredstvennyy.
6. Sathya D., Saravanan G., Thangamani R. Fuzzy logic and its applications in mechatronic control systems //Computational Intelligent Techniques in Mechatronics, 2024. – S. 211-241. – Tekst: neposredstvennyy.
7. Wang W. et al. Development of automatic wheat seeding quantity control system based on Doppler radar speed measurement //Artificial Intelligence in Agriculture, 2025. – T. 15. – №. 1. – S. 12-25. – Tekst: neposredstvennyy.
8. Wang Z. et al. Research on autonomous robots navigation based on reinforcement learning //2024 3rd International Conference on Robotics, Artificial Intelligence and Intelligent Control (RAIIC). IEEE, 2024. – S. 78-81. – Tekst: neposredstvennyy.
9. Yaropud V., Datsiuk D. Innovative methods of increasing the efficiency of selecting plants //Tehnіka, energetika, transport APK, 2024. – № 3 (126). – S. 48-57. – Tekst: neposredstvennyy.
10. Yuqian Z. et al. Optimization design of axial‑flow suction seeder based on response surface methodology and CFD //Journal of Chinese Agricultural Mechanization, 2024. – T. 45. – №. 8. – S. 14. – Tekst: neposredstvennyy.
