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一种自抗扰最优控制器设计方法研究 被引量:9

A Design Method Research of Active Disturbance Rejection Optimal Controller
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摘要 为解决自抗扰控制器参数整定的难题,基于MATLAB免费遗传算法工具箱,对二阶系统自抗扰控制器的5个关键待整定参数进行了整定算法研究;综合考虑控制误差、动态特性和控制能量约束,建立了优化求解的目标函数,并在SIMULINK仿真模型中以离散化形式表达了目标函数并进行了仿真求解:最后对比了基于人工试凑法和遗传算法的自抗扰控制器的控制效果,结果表明,基于遗传算法的自抗扰控制器控制精度更高,超调量更小,控制能量更低,对扰动的预测性能更好。该方法易于实现,可进一步拓宽自抗扰控制的应用范围。 In order to solve the problem of the parameter tuning of the active disturbance rejection controller,a tuning algorithm of the five key parameters of the active disturbance rejection controller for second-order systems is studied based on the free genetic algorithm toolbox of MATLAB.Considering the control error, dynamic characteristics and control energy constraints,the objective function of the optimization is established and expressed in the discrete form in the SIMULINK model.Finally,the control effect of the active disturbance rejection controller based on the artificial test method and genetic algorithm are compared.The results show that the control precision of the active disturbance rejection controller based on genetic algorithm is higher,the overshoot is smaller,the control energy is lower,and the disturbance prediction performance is better.The method is easy to implement,and can further broaden the application range of active disturbance rejection control.
作者 张华 郑加强 ZHANG Hua;ZHENG Jia-qiang(College of Mechanical and Electronic Engineering,Nanjing Forestry University,Nanjing210037,China;Institute of agricultural machinery and intelligent equipment,Anhni Science and Technology University,Fengyang233100,China)
出处 《控制工程》 CSCD 北大核心 2018年第12期2219-2223,共5页 Control Engineering of China
基金 江苏省科技支撑计划-农业高技术专项(BE2012383) 安徽省高校自然科学研究项目(KJ2017A508) 安徽省高校优秀青年人才支持计划重点项目(gxyqZD2018068) 安徽科技学院稳定人才项目(JXWD201701)
关键词 自抗扰控制器 参数整定 遗传算法 目标函数 系统仿真 Active disturbance rejection controller parameter tuning genetic algorithm objective function system simulation
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