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基于复合模糊PID的植保无人机变量喷雾系统设计OA

Design of Plant Protection UAV Variable Spray System Based on Compound Fuzzy PID

中文摘要英文摘要

为提升现有植保无人机喷雾流量随飞行速度变化自适应调整的精准性,降低施药偏差,设计了一种基于复合模糊 PID 控制算法的植保无人机变量喷雾系统,可根据无人机飞行速度,以基于复合模糊 PID 控制算法的 PWM 调制实时调整喷雾流量.通过测试平台分别对比了此控制算法与 PID、模糊 PID 的响应情况,并进行了无人机喷雾流量随飞行速度变化的响应测试.结果表明:基于复合模糊 PID 控制的系统响应较 PID 超调量降低63.64%,较模糊 PID 调节时间缩减 23.08%,复合模糊 PID 与模糊 PID 的稳态误差控制在 3.125%内,小于 PID的 4.688%;基于 PID、模糊 PID、复合模糊 PID 的喷雾系统喷雾流量平均偏差分别为 2.67%、3.85%、1.90%;基于复合模糊 PID 算法的喷雾系统跟随飞速变化自适应调整喷雾流量的最大偏差为 6.29%,满足植保无人机施药作业要求,可为农业航空精准变量喷雾系统设计提供参考.

In order to improve the accuracy of adjusting the spray rate of the existing plant protection UAV with the change of the flight speed and reduce the deviation of pesticide application,this paper designs a plant protection UAV variable spray system based on the compound fuzzy PID control algorithm.The system can adjust the spray flow in real time according to the PWM modulation based on the compound fuzzy PID control algorithm according to the speed of UAV.The response of the control algorithm to PID and fuzzy PID is compared with the test platform,and the response test of UAV spray flux with flight speed is carried out.The results show that the system response based on compound fuzzy PID control is 63.64%lower than PID overshoot and 23.08%shorter than fuzzy PID regulation time.The steady-state error of compound fuzzy PID and fuzzy PID is controlled within 3.125%,which is less than 4.688%of PID;the average deviation of spray flow rate of spray system is 2.67%,3.85%and 1.90%respectively based on PID,fuzzy PID and compound fuzzy PID.Based on the compound fuzzy PID algorithm,the maximum deviation of the spray system fol-lowing the rapid change is 6.29%,which meets the requirements of pesticide application for plant protection UAV.It can provide a reference for the design of agricultural aviation precise variable spray system.

罗明达;邓继忠;霍静朗;张建瓴;叶家杭;雷落成;张子超

华南农业大学 工程学院, 广州 510642||国家精准农业航空施药技术国际联合研究中心, 广州 510642

农业工程

无人机变量喷雾控制算法复合模糊PID

UAVvariable spraycontrol algorithmcompound fuzzy PID

《农机化研究》 2024 (002)

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广东省现代农业产业共性关键技术研发创新团队项目(2020KJ133)

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