基于遗传算法优化模糊PID的甘蔗收获机切割器控制系统
作者:
作者单位:

1.江南大学机械工程学院,无锡 214122;2.江苏省食品先进制造装备技术重点实验室,无锡 214122;3.中国热带农业科学院农业机械研究所/农业农村部热带作物农业装备重点实验室/ 广东省农业类颗粒体精量排控工程技术研究中心/湛江市类颗粒体动力学及精准精量排控重点实验室, 湛江 524091;4.雷州雷宝机械有限公司,湛江 524200

作者简介:

李腾辉,E-mail:1348785278@qq.com

通讯作者:

周德强,E-mail:zhoudeqiang@jiangnan.edu.cn

中图分类号:

TP391.4;S238

基金项目:

湛江市科技发展专项(2020A01005);中央级公益性科研院所基本科研业务费专项(1630132022001);湛江市科技计划项目重点实验室建设专题(2020A05004)


Control system of sugarcane harvester cutter based on fuzzy PID optimized by genetic algorithm
Author:
Affiliation:

1.School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China;2.Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment Technology,Wuxi 214122, China;3.Institute of Agricultural Machinery, Chinese Academy of Tropical Agricultural Sciences/ Key Laboratory of Agricultural Equipment for Tropical Crops, Ministry of Agriculture and Rural Affairs/Guangdong Provincial Research Center for Precision Emission Control of Agricultural Particulates/ Zhanjiang Key Laboratory of Particle Dynamics and Precision Control, Zhanjiang 524091,China;4.Leizhou Leibao Machinery Co., LTD., Zhanjiang 524200, China

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    摘要:

    针对甘蔗收获机切割器无法自动控制入土深度,从而影响收获质量的问题,设计一套甘蔗收获机切割器入土深度自动控制系统。该系统主要包含角度式仿形机构、入土深度检测系统以及液压系统和控制系统。利用基于遗传算法优化的模糊PID控制算法进行入土深度的实时调节,通过Simulink阶跃响应以及带随机干扰的阶跃响应仿真,结果显示:基于遗传算法优化的模糊PID控制算法超调量为4.9%、调节时间为1.535 s,与PID控制算法以及模糊PID控制算法相比均有所改善。室内试验结果表明,基于遗传算法优化的模糊PID控制算法误差在(-0.5,0.5),误差最小,有效实现了切割器入土深度自动控制。

    Abstract:

    A set of automatic control system of sugarcane harvester cutter was designed to solve the problem that the sugarcane harvester cutter cannot automatically control the depth of cutting device, which affects the quality of harvest. The system mainly included angle profile mechanism, depth detection system, hydraulic system and control system. The fuzzy PID control algorithm optimized by genetic algorithm was used to adjust the depth of the soil in real time through Simulink step response and step response with random interference simulation. The results showed that the overshoot of fuzzy PID control algorithm optimized by genetic algorithm was 4.9%. The adjustment time was 1.535 s, being improved compared with PID control algorithm and fuzzy PID control algorithm. The results of comparing laboratory test showed that the error of fuzzy PID control algorithm optimized by genetic algorithm was (-0.5,0.5), which was the smallest, indicating that it automatically control the depth of the cutter effectively.

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李腾辉,周德强,何冯光,邓干然,崔振德,王翔,陈自宏.基于遗传算法优化模糊PID的甘蔗收获机切割器控制系统[J].华中农业大学学报,2023,42(2):243-250

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  • 收稿日期:2022-07-21
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  • 在线发布日期: 2023-03-31
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