Design and Analysis of a Sowing Depth Detection and Control Device for a Wheat Row Planter Based on Fuzzy PID and Multi-Sensor Fusion - Yueyue Li; Bing Qi; Encai Bao; Zhong Tang; Yi Lian; Meiyan Sun (Agronomy, 2025)
A bench test apparatus was developed to address the impact of varying terrain undulation on sowing depth in multi-row wheat sowing machines. In addition, a real-time sowing depth control model was proposed and implemented, enabling automatic adjustment of the sowing depth and ensuring uniform seed placement. The model operates by first specifying a target sowing depth, then acquiring real-time sowing depth measurements via a laser range sensor and terrain feature data ahead of the machine via an array-based LiDAR sensor. These two data streams undergo multi-sensor fusion to produce an accurate error and error rate. A fuzzy PID control algorithm then performs online parameter tuning of the PID gains, generating the control output needed to drive the stepper motor and adjust the depth-limiting wheel height, thereby precisely regulating the sowing depth. Experimental results demonstrate that under representative test conditions, the system achieves excellent sowing depth control performance; average error reductions of 10.7%, 22.9%, and 9.6% were observed when using fuzzy PID control versus no control. This work provides a technical foundation for intelligent sowing depth control in wheat sowing machines and lays the groundwork for future in-field adaptive operation and multi-scenario integrated control.