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<p>The accuracy and real-time adjustment of the header height in traditional wheat combine harvesters is inadequate. To achieve precise adjustment of the combine harvester’s header height, an open-loop transfer function for the header height control system is developed. This paper constructs a simulation model for the combine harvester’s header height using SIMULINK. It employs both the fruit fly optimization algorithm (FOA) and particle swarm optimization (PSO) to optimize the parameters of the proportional-integral-derivative (PID) controller. Multiple types of signals (step signals, sine signals, and random signals) are input into the system to simulate the dynamic response performance of the combine harvester during field operations, and to investigate the optimization effects of these two algorithms on the header height control performance. The results indicate that the step response metrics of the system optimized by the fruit fly optimization algorithm—including overshoot, settling time, and steady-state error—were all reduced. Under step signal input, the overshoot of the system response curve decreased by 35.714 %, the settling time dropped by 27.600 %, and the steady-state error was reduced by 16.667 %. Meanwhile, the average tracking error of the sinusoidal response decreased by more than 31 %, and the fluctuation range of the random response curve also narrowed. As a result, the system based on the fruit fly optimization algorithm exhibits strong robustness when operating conditions change.</p>

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Research on precision control of header height for combine harvesters based on fruit fly optimization algorithm

  • 期刊论文

  • 发表日期：

    2026年4月9日

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  • Chong Wang,
  • Weixin Wu,
  • Xinling Ran,
  • Guoyong Zhang,
  • Weiwei Liu,
  • Yin Shen

摘要

The accuracy and real-time adjustment of the header height in traditional wheat combine harvesters is inadequate. To achieve precise adjustment of the combine harvester’s header height, an open-loop transfer function for the header height control system is developed. This paper constructs a simulation model for the combine harvester’s header height using SIMULINK. It employs both the fruit fly optimization algorithm (FOA) and particle swarm optimization (PSO) to optimize the parameters of the proportional-integral-derivative (PID) controller. Multiple types of signals (step signals, sine signals, and random signals) are input into the system to simulate the dynamic response performance of the combine harvester during field operations, and to investigate the optimization effects of these two algorithms on the header height control performance. The results indicate that the step response metrics of the system optimized by the fruit fly optimization algorithm—including overshoot, settling time, and steady-state error—were all reduced. Under step signal input, the overshoot of the system response curve decreased by 35.714 %, the settling time dropped by 27.600 %, and the steady-state error was reduced by 16.667 %. Meanwhile, the average tracking error of the sinusoidal response decreased by more than 31 %, and the fluctuation range of the random response curve also narrowed. As a result, the system based on the fruit fly optimization algorithm exhibits strong robustness when operating conditions change.