Tillage Depth Detection and Control Based on Attitude Estimation and Online Calibration of Model Parameters

Abstract

Aiming at solving the problems of inaccurate tillage depth detection and unstable tillage depth control, this study proposes a tillage depth detection and control method based on attitude estimation and online calibration of model parameters. First, a tillage depth detection model based on the attitude measurement of the plow is established. The attitude estimation method is designed to measure the horizontal attitude of the plow. An adaptive Kalman filter is utilized to perform an online calibration of the model parameters between the rotation angle of the lifting arm and the pitch angle of the plow. The dynamic and accurate detection of tillage depth is achieved using the tillage depth detection model. Second, a tillage depth control device using an STM32 microcontroller is developed in this study. The PID controller controls the tractor’s suspension system to adjust the plow through the solenoid valve, thus achieving stable control of the tillage depth. Finally, the experimental results obtained from simulation and field tests show that the tillage depth can be stably controlled within the set target interval during the tractor plowing operation, proving the effectiveness and feasibility of the proposed tillage depth detection and control method.