基于增益调度自抗扰控制的变量施药调控方法

Variable spraying control method based on gain scheduling active disturbance rejection control

摘要

针对植保无人机变量施药中的喷雾流量调节时间长、超调量大等问题,提出了一种增益调度线性自抗扰控制(Gain Scheduling Linear Active Disturbance Rejection Control,GSLADRC)方法。基于植保无人机喷雾结构,设计并搭建试验平台,开发变量控制系统,以喷雾流量差值为调度信号,利用动态调整观测器带宽的GSLADRC方法调节喷雾流量,增强控制系统稳定性;然后通过阶跃响应试验,利用Simulink构建系统喷雾流量的仿真模型,对PID、LADRC和GSLADRC方法进行仿真,结果表明GSLADRC控制性能优于其他2种控制方式;最后基于3种控制方法的台架试验结果表明:GSLADRC方法能够快速准确跟踪目标喷雾流量,喷雾流量保持在2%误差范围内的平均调节时间为0.57 s,平均超调量为2.02%,相较于传统PID和LADRC方法,系统喷雾流量调节时间分别降低了35.90%、1.72%,超调量分别降低了80.18%、78.78%,试验期间实际输出与参考流量相对误差小于1%。研究结果表明GSLADRC方法具备良好的喷雾流量调节能力,可为植保无人机变量施药装备研发提供理论依据和技术支持。

Abstract

To address the issues of long spray flow rate settling time and large overshoot in variable spraying of plant protection UAV, a Gain Scheduling Linear Active Disturbance Rejection Control (GSLADRC) method is proposed. Based on the spray system architecture of the plant protection UAV, an experimental platform was developed, and a variable rate control system was developed. Utilizing the spray flow rate error as the scheduling signal, a GSLADRC method with dynamically adjusted observer bandwidth was employed to regulate the spray flow rate, thereby improving the stability of the control system. Through step response experiments, a simulation model of the system's spray flow rate was established in Simulink to simulate the PID, LADRC, and GSLADRC methods. The results demonstrate that the GSLADRC outperforms the other two control strategies. Finally, bench tests were carried out based on three control methods. The experimental results indicate that the GSLADRC method can rapidly and accurately track the target spray flow rate, with an average settling time, within a 2% error band of 0.57 s and an average overshoot of 2.02%. Compared to the conventional PID and LADRC methods, the proposed approach reduced the settling time by 35.90% and 1.72%, and decreased the overshoot by 80.18% and 78.78%, respectively. Furthermore, the relative error between the actual output and the reference flow rate remained below 1% throughout the tests. These results confirm the excellent spray flow rate regulation capability of the GSLADRC method, providing a theoretical foundation and technical support for the development of variable spraying equipment for plant protection UAV.

关键词

植保无人机 / 变量施药 / 自抗扰控制 / 喷雾流量 / 超调量

Key words

plant protection UAV / variable spraying / active disturbance rejection control / spray flow rate / overshoot

[1] 曹光乔,李亦白,南风,等.植保无人机飞控系统与航线规划研究进展分析[J].农业机械学报,2020,51(8):1-16.
Cao Guangqiao, Li Yibai, Nan Feng,et al.Development and analysis of plant protection UAV flight control system and route planning research[J].Transactions of the Chinese Society for Agricultural Machinery,2020,51(8):1-16.
[2] 吴建伟,王秀琴,张文平,等.果园植保无人机精准变量作业控制方法研究[J].中国植保导刊,2024,44(7):11-16.
Wu Jianwei, Wang Xiuqin, Zhang Wenping,et al.Study on precise variable operation control method of orchard plant protection unmanned aerial vehicles[J].China Plant Protection,2024,44(7):11-16.
[3] 顾家冰,丁为民,邱威,等.果园变量施药机械及施药技术研究现状与趋势[J].果树学报,2014,31(6):1154-1157.
Gu Jiabing, Ding Weimin, Qiu Wei,et al.Current research situation and development trend of equipment and technology for orchard spraying[J].Journal of Fruit Science,2014,31(6):1154-1157.
[4] 张萌,张春凤,赵学观,等.变量施药系统压力波动特性及其消除方法研究进展[J].中国农机化学报,2024,45(11):60-68.
Zhang Meng, Zhang Chunfeng, Zhao Xueguan,et al.Research progress on pressure fluctuation characteristics and elimination methods of variable rate spraying system[J].Journal of Chinese Agricultural Mechanization,2024,45(11):60-68.
[5] 牛萌萌,段洁利,方会敏,等.果园施药技术研究进展[J].果树学报,2019,36(1):103-110.
Niu Mengmeng, Duan Jieli, Fang Huimin,et al.Research progress in orchard chemical spraying technology[J].Journal of Fruit Science,2019,36(1):103-110.
[6] 汪欢,毛伟,张亚飞,等.基于水和农药流量同步控制的在线混药系统设计与试验[J].江苏大学学报(自然科学版),2022,43(6):737-744.
Wang Huan, Mao Wei, Zhang Yafei,et al.Design and experiment of online mixing system based on synchronous control of water and pesticide flow[J].Journal of Jiangsu University (Natural Science Edition),2022,43(6):737-744.
[7] 黄胜,朱瑞祥,王艳芳,等.变量施药机的恒压变量控制系统设计及算法[J].农机化研究,2011,33(2):19-22.
Huang Sheng, Zhu Ruixiang, Wang Yanfang,et al.Design and algorithm of constant pressure and variable flow control system of variable pesticide application machine[J].Journal of Agricultural Mechanization Research,2011,33(2):19-22.
[8] 牛顿,马少辉.基于PWM控制的均匀变量喷雾系统设计与台架试验[J].中国农机化学报,2025,46(12):146-153.
Niu Dun,Ma Shaohui.Design and bench test of uniform variable spray system based on PWM control[J].Journal of Chinese Agricultural Mechanization,2025,46(12):146-153.
[9] Luo S Y,Wen S,Zhang L,et al.Extraction of crop canopy features and decision-making for variable spraying based on unmanned aerial vehicle LiDAR data[J].Computers and Electronics in Agriculture,2024,224:109197.
[10] 温鑫伟,马玮,余科松,等.植保无人机实时变量喷洒控制系统设计与试验[J].农机化研究,2024,46(1):90-95.
Wen Xinwei, Ma Wei, Yu Kesong,et al.Design and experiment of real-time variable spraying control system for plant protection UAV[J].Journal of Agricultural Mechanization Research,2024,46(1):90-95.
[11] Wen S,Zhang Q Y,Deng J Z,et al.Design and experiment of a variable spray system for unmanned aerial vehicles based on PID and PWM control[J].Applied Sciences,2018,8(12):2482.
[12] 罗明达,邓继忠,霍静朗,等.基于复合模糊PID的植保无人机变量喷雾系统设计[J].农机化研究,2024,46(2):9-15.
Luo Mingda, Deng Jizhong, Huo Jinglang,et al.Design of plant protection UAV variable spray system based on compound fuzzy PID[J].Journal of Agricultural Mechanization Research,2024,46(2):9-15.
[13] Wang L H,Lan Y B,Yue X J,et al.Vision-based adaptive variable rate spraying approach for unmanned aerial vehicles[J].International Journal of Agricultural and Biological Engineering,2019,12(3):18-26.
[14] 张春凤,张萌,邹伟,等.错相位驱动PWM变量喷雾系统设计与试验[J].农业工程学报,2025,41(16):25-34.
Zhang Chunfeng, Zhang Meng, Zou Wei,et al.Design and experiment of staggered-phase driven PWM variable-rate spray system[J].Transactions of the Chinese Society of Agricultural Engineering,2025,41(16):25-34.
[15] 蒋小平,陈晓飞.基于二阶系统阶跃响应辨识传递函数的实验设计[J].自动化技术与应用,2023,42(2):10-13.
Jiang Xiaoping, Chen Xiaofei.Experimental design of transfer function identification based on step response of second-order system[J].Techniques of Automation and Applications,2023,42(2):10-13.
[16] 王成刚,孙浩,张光胤.基于AMESim微型隔膜泵的动态性能分析[J].机床与液压,2020,48(3):171-175.
Wang Chenggang, Sun Hao, Zhang Guangyin.Dynamic performance analysis of miniature diaphragm pump based on AMESim[J].Machine Tool & Hydraulics,2020,48(3):171-175.
[17] 王举.基于无人飞行器变量喷雾控制系统的设计与研究[D].广州:华南农业大学,2020.
[18] 孙文峰,刘海洋,王润涛,等.基于神经网络整定的PID控制变量施药系统设计与试验[J].农业机械学报,2020,51(12):55-64.
Sun Wenfeng, Liu Haiyang, Wang Runtao,et al.Design and experiment of PID control variable application system based on neural network tuning[J].Transactions of the Chinese Society for Agricultural Machinery,2020,51(12):55-64.
[19] 王东风,朱为琦.线性参数变化系统建模与控制研究进展[J].自动化学报,2021,47(4):780-790.
Wang Dongfeng, Zhu Weiqi.Advances in modeling and control of linear parameter varying systems[J].Acta Automatica Sinica,2021,47(4):780-790.
[20] Gao Z Q.Scaling and bandwidth-parameterization based controller Tuning[C]//Proceedings of the 2003 American Control Conference.Denver,CO,USA:IEEE,2003:4989-4996.
[21] 仇小杰,张宇飞,李业波.辅助动力装置的自抗扰控制方法[J].航空动力学报,2024,39(2):129-137.
Qiu Xiaojie, Zhang Yufei, Li Yebo.Active disturbance rejection control method of auxiliary power unit[J].Journal of Aerospace Power,2024,39(2):129-137.

基金资助

国家自然科学基金项目(32460446),海南省重点研发项目(ZDYF2024GXJS261),新疆生产建设兵团科技计划项目(2025CYL03),海南省重点研发项目(ZDYF2025XDNY126),海南省研究生创新科研课题项目(Qhys2024-221)