基于处方图的油菜精准变量施肥调控系统设计与试验

Design and Experiment of Precise Variable Fertilization Control System for Oilseed Rape Based on Prescription Maps

摘要:

针对目前油菜直播机施肥作业过程中施肥调控精度低、土壤肥力分布不同难以实现时空差异化肥力补给的问题，设计了一种基于处方图的油菜精准变量施肥线性自抗扰调控系统。提出了基于云端高精度地图规划作业路径对施肥处方图进行栅格划分的方法，为机具施肥提供了指导性施肥量。构建了排肥器的线性自抗扰控制算法，Matlab仿真确定了关键参数，并与PID控制算法对比，线性自抗扰控制算法在抗干扰、超调量、稳态误差分别提高了39.08%、91.77%、86.96%。台架试验结果表明：施肥调控系统在设定施肥量和作业速度下，排肥器颗粒肥排量平均控制精度为98.06%。路面试验结果表明：基于处方图的变量施肥调控系统在变量施肥作业时，通过滞后距离补偿，平均施肥位置滞后距离为0.28 m，不同位置的施肥量控制精度均大于95.67%。田间试验结果表明：线性自抗扰控制算法在不同栅格区域内施肥量控制精度不低于95.21%，优于PID控制算法。该研究可为油菜生产中基于土壤养分的精准变量施肥提供技术支持。

Abstract:

Aiming at the current reality of low accuracy of fertilizer regulation and control during the fertilizer application operation of oilseed rape direct seeding machine, and the difficulty of realizing spatiotemporal differentiated fertilizer replenishment with different soil fertility distributions, an accurate variable fertilizer application linear self-resistant regulation and control system was designed-based on the prescription map for oilseed rape. A method of raster division of the fertilizer prescription map-based on the cloud-based high-precision map planning operation path was proposed, which provided a guiding fertilizer amount for the machine fertilizer application. A linear self-immunity control algorithm for fertilizer dischargers was constructed. Matlab simulation determined the key parameters, and comparison with the PID control algorithm showed that the linear self-immunity control algorithm improved the anti-interference, overshooting amount, and steady-state error by 39.08%, 91.77%, and 86.96%, respectively, compared with the latter. The results of the bench test showed that the average control accuracy of the fertilizer dispenser’s granular fertilizer discharge was 98.06% under the set fertilizer application rate and operating speed of the fertiliser application regulation system. The road test results indicated that the prescription map-based variable fertilization control system, after compensating for lag distance during variable fertilization operations, achieved an average fertilization position lag distance of 0.28 m, with the control accuracy of fertilizer application volume exceeding 95.67% across different positions. The results of the field test showed that the linear self-immunity control algorithm had a control accuracy of no less than 95.21% of the fertilizer amount in different grid areas, which was better than the PID control algorithm. The research result can provide an effective reference for accurate variable fertilizer application-based on soil nutrients in oilseed rape production.