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Journal of Chinese Agricultural Mechanization

Journal of Chinese Agricultural Mechanization ›› 2025, Vol. 46 ›› Issue (3): 87-92.DOI: 10.13733/j.jcam.issn.2095-5553.2025.03.014

• Facilities Agriculture and Plant Protection Machinery Engineering • Previous Articles     Next Articles

Research on variable spraying control system based on improved whale optimization PID algorithm 

Qin Jibiao1, 2, Chen Longbin1, Bao Difa1, Zheng Shuhe1, 2   

  1. (1. College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University, Fuzhou, 350002, China;
    2. Modern Agricultural Equipment Fujian University Engineering Research Center, Fuzhou, 350002, China)
  • Online:2025-03-15 Published:2025-03-12

基于改进鲸鱼优化PID算法的变量喷药控制系统研究

秦吉彪1, 2,陈龙彬1,鲍地发1,郑书河1, 2   

  1. (1. 福建农林大学机电工程学院,福州市,350002; 2. 现代农业装备福建省高校工程研究中心,福州市,350002)
  • 基金资助:
    福建省科技计划项目(2022N0009)

Abstract:

n order to solve the problem of poor real-time and low accuracy of the traditional PID control method, and to realize the automatic adjustment of the PID control parameters, this paper combines the Improved Whale Optimization Algorithm (IWOA) with PID control, and designs a variable spraying control system based on the Improved Whale Optimization PID Algorithm (IWOA—PID). Meanwhile, the mathematical model of transfer function of variable spraying control system was constructed, and MATLAB was used to simulate the variable spraying control system and build a spraying test bed for experimental verification. The simulation results show that the performance index of IWOA—PID control is better than the traditional PID control, the system overshoot is reduced from 1.39% to 0.10%, the steady state error is reduced from 1.19% to 0, and the regulation time is reduced from 1.072 s to 0.806 s. The experimental results show that the system response of the IWOA—PID control is faster, with an average response time of 2.98 s, while the average system response time of the PID control is 4.46 s. The average steady state error is also reduced from 17.1% to 11.3%. This method can better meet the demand for real-time and accuracy in agricultural production, and provides a new way for the research of variable spraying technology.

Key words: variable spraying, improved whale optimization algorithm, PID control, parameter optimization, control system

摘要:

为解决传统PID控制方法实时性差与准确性低的问题,实现PID控制参数的自动整定,将改进的鲸鱼优化算法(IWOA)与PID控制相结合,设计一种基于改进鲸鱼优化PID算法(IWOA—PID)的变量喷药控制系统。同时,构建变量喷药控制系统传递函数数学模型,利用MATLAB对变量喷药控制系统进行仿真试验并搭建喷药试验台进行试验验证。仿真结果表明:相比于传统PID控制,IWOA—PID控制系统超调量由1.39%减少到0.10%,稳态误差由1.19%减小到0,调节时间由1.072 s减少到0.806 s。试验结果表明:IWOA—PID控制的系统响应更快,平均响应时间为2.98 s,而PID控制的平均系统响应时间为4.46 s;平均稳态误差由17.1%减小到11.3%。该方法能够较好地满足农业生产中对实时性与准确性的需求,为变量喷药技术的研究提供新途径。

关键词: 变量喷药, 改进鲸鱼优化算法, PID控制, 参数优化, 控制系统

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