Design of Dynamic Deep Sowing System for Peanut Planter with Double-Loop Feedback Fuzzy PID Control

To enhance peanut sowing depth consistency, an active depth adjustment planter was designed. This study employs inclination and pressure sensors for ridge surface detection, coupled with a hydraulic cylinder and profiling mechanism to dynamically adjust furrow depth according to ground variations. A mathematical model integrating detection, adjustment, and execution processes was established. The control system adopts an improved DLF-Fuzzy PID (double-loop feedback fuzzy PID) control strategy, with co-simulation in MATLAB/AMESIM for performance comparison. The results demonstrate the improved algorithm’s superiority in sowing depth accuracy. Field experiments evaluated three operational parameters (vehicle speed, pressure, and sowing depth) with the qualification rate as the metric. At 50 mm sowing depth and 3 km/h speed, the system achieved a 94.6% dynamic qualification rate and 2.38% maximum depth variation coefficient. Compared with existing methods, this approach enhances sowing depth control effectiveness by 6.05% and reduces variation by 2.85%.

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Publication Details

Journal
Agriculture
Published
2025-04-08
DOI
https://doi.org/10.3390/agriculture15080808
Citations
2
Primary Topic
Soil Mechanics and Vehicle Dynamics
Type
article
Field-Weighted Citation Impact
1.91
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article

Design of Dynamic Deep Sowing System for Peanut Planter with Double-Loop Feedback Fuzzy PID Control

Yaqing Gu, Ping Wang, Shuqi Shang, Moxian LI et al.
2 citations
Agriculture
Soil Mechanics and Vehicle Dynamics
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article

Design of Dynamic Deep Sowing System for Peanut Planter with Double-Loop Feedback Fuzzy PID Control

Yaqing Gu, Ping Wang, Shuqi Shang, Moxian LI, Xueliang Chang
article en
2 citations

Abstract

To enhance peanut sowing depth consistency, an active depth adjustment planter was designed. This study employs inclination and pressure sensors for ridge surface detection, coupled with a hydraulic cylinder and profiling mechanism to dynamically adjust furrow depth according to ground variations. A mathematical model integrating detection, adjustment, and execution processes was established. The control system adopts an improved DLF-Fuzzy PID (double-loop feedback fuzzy PID) control strategy, with co-simulation in MATLAB/AMESIM for performance comparison. The results demonstrate the improved algorithm’s superiority in sowing depth accuracy. Field experiments evaluated three operational parameters (vehicle speed, pressure, and sowing depth) with the qualification rate as the metric. At 50 mm sowing depth and 3 km/h speed, the system achieved a 94.6% dynamic qualification rate and 2.38% maximum depth variation coefficient. Compared with existing methods, this approach enhances sowing depth control effectiveness by 6.05% and reduces variation by 2.85%.

AgricultureVol. 15(8)
Qingdao Agricultural University (CN)
Openalex Percentile: Top 16%
Soil Mechanics and Vehicle Dynamics
1.91
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