水稻液体肥变量施用调节系统设计与试验

    Design and experiment on the variable application regulation system of liquid fertilizer in rice

    • 摘要:
      目的 设计一种机电式流量调节阀,与已研制的气力引射式施肥器集成构建液体肥变量施用调节系统,实现水稻近根部微小流量液体肥精准施用。
      方法 通过试验标定了系统质量流率理论模型,建立控制系统传递函数模型,设计了基于模糊推理的PID控制器结构、规则和初始参数;通过仿真试验,分析了PID和模糊PID控制的调控响应能力。
      结果 仿真试验结果表明,模糊PID控制阶跃信号响应超调量、调节时间和稳态误差分别为0.12%、2.51 s和0.007, 与PID控制的对应值42.90%、4.44 s和0.010相比均较低,表明模糊PID控制动态调节和稳定性更好;在幅值为0.5、持续时间为0.1 s的脉冲信号干扰下,模糊PID控制的调节时间为0.61 s,比PID控制(1.67 s)更短,具有更强的抗干扰能力。性能试验结果表明,10种目标质量流率条件下,模糊PID控制的质量流率绝对误差均低于PID控制,控制精度为93.93%~96.88%,高于PID控制(90.00%~95.21%);在施肥量变化时,模糊PID控制的超调量为12.2%,上升时间、调节时间和峰值时间分别为1.5、10.7和1.7 s均低于PID控制的17.4%、2.1 s、13.3 s和2.3 s。
      结论 基于模糊PID控制的水稻液体肥变量施用调节系统具有较高的质量流率控制精度和跟踪性能,为研制水稻田液体肥变量施肥装备奠定了基础。

       

      Abstract:
      Objective In order to achieve accurate application of micro flow liquid fertilizer near rice root, an electromechanical flow regulating valve was designed and integrated with the developed pneumatic ejector fertilizer applicator to construct a variable application regulation system of liquid fertilizer.
      Method The theoretical model of system mass flow rate was calibrated through experiments, and the transfer function model of control system was established. The structure, rules and initial parameters of the PID controller based on fuzzy reasoning (fuzzy PID control) were designed. The regulatory response capabilities of PID control and fuzzy PID control were compared through simulation experiment.
      Result The simulation experimental results showed that the overshoot, adjustment time, and steady-state error of step signal response for fuzzy PID control were 0.12%, 2.51 s, and 0.007 respectively, which were lower than 42.9%, 4.44 s, and 0.010 of PID control, and suggested fuzzy PID control had better dynamic adjustment and stability. Under interference of pulse signal with amplitude of 0.5 and duration of 0.1 s, the adjustment time of fuzzy PID control was 0.61 s, which was less than 1.67 s of PID control, and had stronger anti-interference ability. The performance test showed that under ten-target mass flow rate condition, the absolute error of mass flow rate of fuzzy PID control was lower than that of PID control, with a control accuracy of 93.93% to 96.88%, which was higher than 90.00% to 95.21% accuracy of PID control. When the fertilizer amount changed, the average overshoot was 12.2%, and rise time, adjustment time and peak time of fuzzy PID control were 1.5, 10.7 and 1.7 s respectively, which were lower than 17.4%, 2.1 s, 13.3 s and 2.3 s of PID control.
      Conclusion The variable rate application and regulation system for liquid fertilizer in rice based on fuzzy PID control has higher quality flow rate control accuracy and tracking performance, laying a foundation for the development of variable rate fertilizer equipment for liquid fertilizer in rice field.

       

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