Design and Experiment of Profiling Pickup Control System for Peanut Pickup Harvester

To address the issues of high missed-pickup loss caused by ground undulations and the high labor intensity of manual adjustment during peanut pickup harvesting, this study proposed a profiling pickup control system for peanut pickup harvesters based on the synergy of multi-sensor fusion and a fuzzy PID control algorithm. To ultimately determine the optimal operating height, a wheeled profiling device equipped with an angle sensor was utilized to detect the ground clearance of the pickup header, corrected in combination with an inclination sensor. A mechanical–electrical–hydraulic co-simulation was conducted using Amesim and Matlab/Simulink to comparatively analyze the control performance of conventional PID and fuzzy PID. The simulation results demonstrated that fuzzy PID control exhibited superior performance in reducing height errors and enhancing overall operational stability, showing better adaptability. Field trials were conducted across multiple sets of working conditions, operating speeds, and pickup heights. The experimental results indicated that under fuzzy PID control, the average response speeds for lifting and lowering the pickup header were 0.29 m/s and 0.23 m/s, respectively, representing increases of 52.6% and 76.9% compared to conventional PID control. Across different forward speeds and operating conditions, the average control accuracy of fuzzy PID control reached 95.2%, an improvement of 1.2 percentage points over PID control. The average peanut pickup rate reached 99.3%, 0.3 percentage points higher than that achieved by manual adjustment. This control system demonstrates high reliability and provides technical support for the intelligent, low-loss pickup harvesting of peanuts.