考虑边端效应的直线感应电机投影自适应指令滤波反推控制
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作者单位:

(江南大学物联网工程学院,江苏无锡214122)

作者简介:

颜文旭(1971-), 男, 副教授, 博士, 从事电机驱动控制技术、电力电子等研究;许德智(1985-), 男, 副教授, 博士, 从事数据驱动控制、故障诊断与容错控制、新能源控制技术等研究.

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E-mail: lutxdz@126.com

中图分类号:

TP273

基金项目:

国家自然科学基金项目(61503156,61403161);中央高校科研计划重点项目(JUSRP11562,NJ20150011);国家重点研发计划项目(2016YFD0400301).


Projection-based adaptive command-filtered backstepping control for linear induction motor considering end effect
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(School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China)

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    摘要:

    针对考虑边端效应的直线感应电机精确位置跟踪问题,设计一种基于间接矢量控制的投影自适应指令滤波反推控制器.首先,给出间接矢量控制下考虑边端效应的直线感应电机模型;其次,运用反推法设计控制器,同时采用限幅的指令滤波器处理反推法中计算膨胀和控制器饱和问题,并对指令滤波器产生的滤波误差设计补偿信号;然后,基于李雅普诺夫稳定性理论设计自适应律,估计直线感应电机控制系统中的不确定参数(移动物件的总质量、粘滞系数、外部的负载扰动),并引入投影算子保证估计值的有界性;最后,将所设计的控制器分别与传统PID控制器、指令滤波反推控制器对比.仿真结果表明,所设计的控制器具有更强的动态性能、抗干扰性及鲁棒性.

    Abstract:

    A projection-based adaptive command-filtered backstepping controller is designed based on indirect vector control to deal with the problem of position tracking of the linear induction motor(LIM) considering end effects.Firstly, the dynamic model of indirect vector control of the LIM considering end effects is presented.Then, backstepping is used to design virtual controllers step by step, meanwhile, constrained command filters are used to solve the differential expansion and the controller input saturation in the traditional backstepping, and compensating signals are designed to reduce the effect of the filtering errors caused by command filters.Furthermore, adaptive laws are designed to estimate uncertain parameters (unknown total mass of the mover, viscous friction and external load disturbance) in the LIM, and projection operator is introduced to ensure the boundedness of the estimated parameters.Finally, simulation results demonstrate that the proposed controller has more excellent dynamic performance and stronger robustness compared with the traditional proportional-integral-derivative(PID) controller and command-filtered backstepping controller(CBC).

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颜文旭,黄杰,许德智.考虑边端效应的直线感应电机投影自适应指令滤波反推控制[J].控制与决策,2018,33(8):1399-1406

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  • 在线发布日期: 2018-07-26
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