Optimal Estimation of Seedlings Replanting Device Control Based on Kalman Filter

The stepping motor for the seedlings replanting device is inaccurate in speed feedback control precision and the median filtering cannot dispel the interference random error. This paper proposes the Kalman filter algorithm to realize the filter estimation of the encoder speed value. The average angular velocity omega(b) is the expected value of the stepper motor angular velocity control. The results show that Kalman filtering can effectively achieve data filtering for uncertain random signals considering the observation noise and process noise. The results of the seedlings replanting test showed that when the planting frequency was 40 plants/min and 50 plants/min, the success rate of seedling detection and seedling success rate were as high as 100%, and when the planting frequency was increased to 60 plants/min, the seedling speed of the seedling needles became faster, and the failure of the fiber-optic sensor leak detection failed, resulting in a 95.80% success rate of seedling detection success rate and seedling recovery.