Feeding rail cars are indispensable in the feeding link of modern fishery breeding, in order to solve the problems of low accuracy of the motion displacement model of the fish pond feeding railcar and the complex operation of the human-computer interaction system, a railcar drive control system based on automation and machine learning technology was designed. With PLC as the core controller, a DTU is integrated to realize remote control. The whole process of automatic feeding operation was written in LAD language. The motion displacement of the small railcar is recorded by using the proximity switch and RFID locator, and the motion displacement model is fitted by the Lasso Regression Algorithm. Based on HMI language, a human-computer interaction system was developed to arrange information and data such as motion displacement models, operation buttons, and indicator arranged in a 'pin' - shaped layout for intuitive information display. The results showed that the mean square error (MSE) of the fitted motion displacement model was 20.7449, the mean absolute error (MAE) was 3.0849, and the coefficient of determination (R2) was 0.9892. The proportion of users who were satisfied with the evaluation indexes of the human-computer interaction system was more than 90%. The average Frecher distance coefficient of the gear speed change curve of the three full-process positioning feeding operations was 9.289. The drive control system operates stably and reliably, and can better meet the actual production needs.
