Peanut seeding depth control system based on MLE-KF and fuzzy PID control

Aiming at the problem that the consistency and stability of seeding depth are difficult to control during the complex field operation of peanut seeders, this study proposes a control method combining the Kalman Filter algorithm based on Maximum Likelihood Estimation (MLE-KF) and the Fuzzy PID algorithm. A system was designed to automatically adjust the furrow opener during the operation of the peanut seeder, thereby realizing the automatic control of seeding depth. This method maintains the peanut seeding depth within a reasonable error range suitable for growth, and effectively ensures the consistency of peanut seeding depth. In this study, displacement sensors and ultrasonic sensors were used to directly or indirectly detect the furrow depth. Combined with electric push rods and actuators, the furrow depth was adjusted in real time during the field operation of the peanut seeder. For the filtering fusion algorithm, a noise parameter adaptive algorithm based on sliding window and approximate MLE was adopted, while a Fuzzy PID control strategy was employed for the controller. Simulations were conducted in MATLAB/Simulink, and the simulation results showed that the improved algorithm achieved a significant improvement in seeding depth accuracy compared with the traditional Kalman Filter and PID control. Field tests were carried out with the qualification rate as the index under different operating speeds and seeding depth conditions. For this seeding depth control method, when the operation speed was 3 km/h and the furrow depth was set to 50.00 mm, the qualification rate of seeding depth reached 94.80%, with a standard deviation of 3.12 mm and a coefficient of variation of 6.08%. Compared with the traditional mechanical adjustment and passive adjustment methods, this method increased the qualification rate by 4.60% and 3.30%, respectively, and reduced the coefficient of variation by 2.46% and 3.01%, respectively. The research on the seeding depth control method in this study provides a new detection and control approach for the seeding depth control of peanut seeders.