Based on Fuzzy PID Simulation Analysis of the Sugarcane Seeder Planting Control System

In response to the problems of low operation efficiency and poor uniformity of seed distribution in traditional sugarcane sowing machines, this study proposes an intelligent seed distribution system solution based on fuzzy PID control. Through an innovative method combining multi-body dynamics modeling and discrete element simulation, the dynamic mathematical model of the sowing mechanism was systematically constructed: Firstly, the dynamic equation of the seed distribution mechanism was established based on the multi-body dynamics theory, then the seed flow characteristic parameters were obtained through discrete element simulation, and finally the second-order lag system transfer function was established through parameter identification. In response to the shortcomings of traditional PID control, such as large overshoot and long adjustment time, a real-time optimization strategy for PID parameters based on fuzzy rules was proposed. By dynamically adjusting the proportional, integral, and derivative parameters, the closed-loop control of sowing accuracy was achieved. The simulation results show that the improved Fuzzy-PID control effectively solves the problem of insufficient adaptive control ability of traditional machinery compared with traditional PID control. It innovatively couples the intelligent control algorithm with agronomic parameters, providing a theoretical basis and technical support for precise sowing of economic crops such as sugarcane, and has important engineering application value for promoting the intelligent development of intelligent agricultural equipment.