Design and Testing of an Intelligent Control System for Maize Picking Harvest

Abstract

The driving tasks of a maize harvester are exhausting because of the varying soil, maize conditions, and the long working time. Operators must adjust and optimize the internal settings of the harvester to modify the working parameters and reduce the harvest loss. In this paper, an intelligent control system for maize picking harvest was investigated for automatic adjustment and minimization of maize picking losses. A prediction model based on experimental data was used to predict the maize picking loss rate, and the rotational speed of the pulling rollers, operating speed, and header height were optimized to minimize the maize picking loss. The intelligent control system allows use of manual or automatic controls; the controller adjusts the rotational speed of pulling rollers, the operating speed, and header height based on the measured picking losses in automatic mode. The designed automatic control system comprises faster and slower loops. The fuzzy proportional–integral–derivative (PID) method is used to optimize the rotational speed of pulling rollers and the operating speed in the faster loop, and the PID method is used to regulate the header height in the slower loop. Field experiments were conducted to evaluate the effectiveness and stability of the system. The system test results showed that all working parts respond quickly, and the overshoot and steady-state errors of each working part were relatively small. Regardless of the load condition, the established control strategy could optimize each working parameter of the maize harvester. In experiments, maize picking loss rates of 1.676% and 1.386% were obtained, which meet the requirements of maize harvesting.