| 卡尔曼滤波融合遗传PID控制算法在提高播种精度中的应用 |
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| 引用本文： | 刘伟,马彪,马利强,陈雪辉,俞传阳,黄磊,李昊.卡尔曼滤波融合遗传PID控制算法在提高播种精度中的应用[J].安徽农业大学学报,2021,48(4):674-679. |
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| 作者姓名： | 刘伟 马彪 马利强 陈雪辉 俞传阳 黄磊 李昊 |
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| 作者单位： | 安徽建筑大学机械与电气工程学院,合肥230601 |
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| 基金项目： | 安徽省高校协同创新项目（GXXT-2019-036）, 安徽建筑大学引进人才及博士启动基金项（2018QD16）, 安徽省科技重大专项（18030701197）和安徽建筑大学校级科研项目（JZ192083）共同资助。 |
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| 摘 要： | 为提高排种器的排种精度,在传统气吸式排种盘转速控制的基础上,设计了一套卡尔曼滤波融合遗传PID控制算法,通过PID控制算法实现排种盘电机转速的闭环控制,通过卡尔曼滤波算法滤除排种盘在转动过程中因振动和外界干扰等原因产生的噪声,并采用遗传算法快速准确的寻找PID控制过程中的最优控制参数.为验证算法的有效性,假设输入信号为单位阶跃信号,并在噪声大小为0.002和0.1的情况下分别进行了实验.在噪声为0.002时,传统PID控制响应波动值可达到1.5,遗传PID控制响应波动值最大仅为1.2;加入卡尔曼滤波后,传统PID控制输出响应趋于稳定的时间约为0.2 s,遗传PID控制的输出响应趋于稳定的时间约为0.08 s;同理,将噪声增大为0.1后,采用相同的实验方案进行实验,最终实验说明了卡尔曼滤波融合遗传PID控制算法在提高排种盘电机转速稳定性中的有效性.
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| 关 键 词： | PID控制 卡尔曼滤波 遗传算法 播种精度 |
| 收稿时间： | 2020/11/5 0:00:00 |
Application of Kalman filter combined with genetic PID control algorithm in improving seeding accuracy |
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| LIU Wei,MA Biao,MA Liqiang,CHEN Xuehui,YU Chuanyang,HUANG Lei,LI Hao.Application of Kalman filter combined with genetic PID control algorithm in improving seeding accuracy[J].Journal of Anhui Agricultural University,2021,48(4):674-679. |
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| Authors: | LIU Wei MA Biao MA Liqiang CHEN Xuehui YU Chuanyang HUANG Lei LI Hao |
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| Institution: | School of Mechanical and Electrical Engineering , Anhui Jianzhu University, Hefei 230601 |
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| Abstract: | For improving the precision of seed metering device, a set of Kalman filter combined with genetic PID control algorithm is designed based on the speed control of traditional air suction seed metering plate. The closed-loop control of motor speed of seed metering plate is realized by PID control algorithm, and the noise caused by vibration and external interference is filtered out by Kalman filter algorithm, and genetic algorithm is adopted quickly and accurately to find the optimal control parameters in the process of PID control. In order to verify the effectiveness of the algorithm, the input signal is assumed to be a unit step signal, and the experiments are carried out under the noise level of 0.002 and 0.1 respectively. When the noise is 0.002, the response fluctuation value of traditional PID control can reach 1.5, while the maximum response fluctuation value of genetic PID control is only 1.2; after adding a Kalman filter, traditional PID control has a stable output response for about 0.2 s, and that of genetic PID control is about 0.08 s; similarly, when the noise is increased to 0.1, the same experimental scheme is adopted. Finally, the experiment shows the effectiveness of Kalman filter combined with genetic PID control algorithm in improving the speed stability of seed metering disk motor. |
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| Keywords: | PID control Kalman filter genetic algorithm sowing precision |
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