基于BLDCM的智能播种控制系统设计
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摘要
针对地轮驱动的玉米排种工作方式存在地轮打滑而造成漏播率增加的问题,设计了基于无刷直流电机驱动(Brushless Direct Current Motor,BLDCM)的智能播种控制系统。该系统以STM32单片机作为PID控制器的核心处理器,利用无刷直流电机作为排种器驱动源,并通过增量式编码器实时采集排种器的转速,同时利用霍尔传感器获取播种作业速度。为实现PID控制的最优化,在Simulink环境下建立无刷直流电机的仿真模型,并结合PSO(Particle Swarm Optimization,粒子群优化)算法对PID参数进行优化设计。仿真结果表明:经PSO整定后,PID控制器的阶跃响应效果良好,超调量为4%,调节时间为0.12s。田间试验结果表明:在低速、中速、高速和变速作业条件下,本电机驱动系统较传统地轮驱动系统在漏播指数方面分别降低了0.9%、1.1%、1.4%和1.3%,在播种合格指数方面分别提高了1.8%、3.8%、2.8%和1.7%。
An intelligent seeding control system based on Brushless Direct Current Motor( BLDCM) is designed to solve the problem of the increasing rate of missing seeding caused by the slide of the land wheel during sowing work. In this system,we use a STM32 microcontroller as the core processor of the PID controller,using the BLDCM as a drive source for the seed metering device,collecting the speed of the seed metering device through a incremental encoder,and using the Hall sensor to obtain the sowing speed. In order to realize the PID control optimization,a simulation model of BLDCM is established in the simulink integrated development environment,and the PID parameters are optimized by PSO( Particle Swarm Optimization) algorithm. The simulation results show that the PID controller after PSO tuning has a good step response,the overshoot is 4%,and the adjustment time is 0. 12 s. Field test results show that in the condition of low speed,medium speed,high speed and variable speed operation,the miss index of the motor drive system designed in this paper is 0. 9%,1. 1%,1. 4% and 1. 3% lower than that of the traditional wheel drive system respectively,and enhancing 1. 8%,3. 8%,2. 8% and 1. 7% in the seeding qualified index respectively.
An intelligent seeding control system based on Brushless Direct Current Motor( BLDCM) is designed to solve the problem of the increasing rate of missing seeding caused by the slide of the land wheel during sowing work. In this system,we use a STM32 microcontroller as the core processor of the PID controller,using the BLDCM as a drive source for the seed metering device,collecting the speed of the seed metering device through a incremental encoder,and using the Hall sensor to obtain the sowing speed. In order to realize the PID control optimization,a simulation model of BLDCM is established in the simulink integrated development environment,and the PID parameters are optimized by PSO( Particle Swarm Optimization) algorithm. The simulation results show that the PID controller after PSO tuning has a good step response,the overshoot is 4%,and the adjustment time is 0. 12 s. Field test results show that in the condition of low speed,medium speed,high speed and variable speed operation,the miss index of the motor drive system designed in this paper is 0. 9%,1. 1%,1. 4% and 1. 3% lower than that of the traditional wheel drive system respectively,and enhancing 1. 8%,3. 8%,2. 8% and 1. 7% in the seeding qualified index respectively.
引文
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[2]史嵩,张东兴,杨丽,等.气压组合孔式玉米精量排种器设计与试验[J].农业工程学报,2014,30(5):10-18.
[3]刘佳,崔涛,张东兴,等.机械气力组合式玉米精密排种器[J].农业机械学报,2012,43(2):43-47.
[4]杜荣华,朱昭,舒雄,等无刷直流电动机自适应模糊PID控制及仿真[J].长沙理工大学学报,2014,11(2):60-66.
[5]张军,时培成,彭闪闪.基于Matlab/Simulink的无刷直流电机控制系统建模与仿真[J].井冈山大学学报:自然科学版,2016,37(1):85-91.
[6]张春岭,吴荣,陈黎卿.电控玉米排种系统设计与试验[J].农业机械学报,2017,48(2):51-59.
[7]吴一欣,廖军辉.无刷直流电机转矩脉动抑制研究[J].计算机仿真,2009,26(10):365-369.
[8]于晓敏,于晓坤,耿蕊.PID控制器参数优化算法的仿真研究[J].计算机仿真,2011,28(7):212-215.
[9]张奎,雷勇.无刷直流电机智能PID控制系统建模与仿真[J].测控技术,2015,34(4):81-84.
[10]朱红萍,罗隆福,朱红萍.基于ITAE指标的PID控制器参数优化设计[J].电气自动化,2009,31(6):37-19.
[11]徐峰,李东海,薛亚丽.基于ITAE指标的PID参数整定方法比较研究[J].中国电机工程学报,2003,23(8):206-210.
[12]张丹,韩胜菊,李建,等.基于改进粒子群算法的BP算法的研究[J].计算机仿真,2011,28(2):147-150.
[13]任子晖,王坚.一种动态改变惯性权重的自适应粒子群算法[J].计算机科学,2009,36(2):227-256.
[14]罗卫兵,胡健生.基于STM32+uc GUI的北斗导航定位系统设计[J].液晶与显示,2014,29(2):195-201.