Adaptive negative-pressure control system for electric-driven seeding blowers based on a DILPSO-fuzzy PID controller

文献类型： 外文期刊

第一作者： He, Kangkang

作者： He, Kangkang;Chen, Jincheng;Pan, Feng;Wang, Baiwei;Ji, Chao;He, Kangkang;He, Kangkang;Chen, Jincheng;Pan, Feng;Wang, Baiwei;Ji, Chao

作者机构：

关键词： Negative pressure control; Fuzzy PID; Particle swarm optimization; Adaptive control

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：8.9； 五年影响因子：9.3 ）

ISSN： 0168-1699

年卷期： 2025 年 239 卷

页码：

收录情况： SCI

摘要： Maintaining stable negative pressure in air-suction seeders is crucial for minimizing the energy consumption, reducing the seed damage, and enhancing the seeding efficiency. In this study, we designed an adaptive negative pressure control system based on dynamic inertia learning particle swarm optimization (DILPSO)-fuzzy proportional-integral-derivative (PID) to address the issue of significant negative pressure fluctuations and the inability to adaptively adjust with the seeding speed during the operation. We optimized the fuzzy PID controller using the DILPSO algorithm, dynamically adjusted the inertia weight and learning factor according to the number of iterations, and established the control simulation model. The simulation outcomes indicate that, when compared with conventional PID and fuzzy PID controllers, the DILPSO-fuzzy PID controller exhibited superior performance in terms of the response speed, robustness, and tracking error. We employed the bench test to determine the negative pressure measurement position, the optimal negative pressure corresponding to the sowing speed, and the control parameters. The results indicate that the DILPSO-fuzzy PID control system can effectively reduce the negative pressure fluctuation. We conducted field experiments to verify the seeding operation effect of the system under the random speed condition of 6-8 km/h. The proposed controller presented better seeding performance when compared with other control methods. Its qualified seeding index reached 92.12 %, and the missed seeding rate and reseeding rate were 2.50 % and 5.38 %, respectively. In summary, the DILPSO-fuzzy PID control system can effectively reduce the negative pressure fluctuations and adaptively change with the operation speed, thereby meeting the design requirements of high control accuracy, stability, rapidity, and anti-interference. These findings present a theoretical foundation and practical reference for adaptive negative pressure control in electric-driven blowers of air-suction seeders.

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