直流电机神经元PID调速系统设计与仿真  被引量:11

Design and Simulation of DC Motor Speed Regulation System Based on Neuron PID Controller

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作  者:周晓华[1,2] 蓝会立[1,2] 张银[1,3] 李振强[1] ZHOU Xiao-hua LAN Hui-li ZHANG Yin LI Zhen-qiang(School of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou,Guangxi 545006,China Guangxi key laboratory of Automobile Components and Vehicle Technology,Guangxi University of Seience and Technology, Liuzhon,Guangxi 545006,China Key Laboratory of Indnstrial Process Intelligent Control Teohnology of Guanxi Higher Eduction Instites,Guangxi University of Science and Technology,Liuzhou,Guangxi 545006,China)

机构地区:[1]广西科技大学电气与信息工程学院,广西柳州545006 [2]广西汽车零部件与整车技术重点实验室(广西科技大学),广西柳州545006 [3]广西高校工业过程智能控制技术重点实验室(广西科技大学),广西柳州545006

出  处:《计算技术与自动化》2017年第1期23-26,共4页Computing Technology and Automation

基  金:广西自然科学基金项目(2013GXNSFCA019020);广西汽车零部件与整车技术重点实验室自主研究课题(15-A-02-01);广西高校工业过程智能控制技术重点实验室主任基金(IPICT-2016-06)

摘  要:针对传统PI双闭环直流电机调速系统存在响应速度慢、超调量大、抗干扰能力及自适应能力差等问题,提出了一种双闭环直流电机调速系统的神经元PID转速调节器设计方法。该转速调节器采用神经元控制器和比例控制相结合进行设计,从而构成了一种具有自学习、自适应能力的神经元PID控制器,然后与传统单神经元PID设计的转速调节器控制效果进行了对比。结果表明,基于神经元PID转速调节器的双闭环直流电机调速系统具有较快的响应速度、良好的动态和静态稳定性、较强的自适应能力和抗干扰能力。The DC motor double closed loop speed regulation system based on the traditional PI controller has slow re- sponse speed, large overshoot, poor anti-interference ability and adaptive ability, so a design method of speed regulator based on neuron adaptive PID was proposed. The speed regulator was designed by using neuron controller and proportional controller. It is a neuron PID controller with self-learning and adaptive ability. Then, the control effect was compared with speed regulator based on the traditional single neuron PID controller. The simulation results show that DC motor double closed loop speed regulation system based on neuron adaptive PID has faster response speed, better static and dynamic regu- lation stability, stronger anti-interference ability and adaptive ability.

关 键 词:直流电机 转速调节器 神经元控制 比例控制 神经元PID 

分 类 号:TM331[电气工程—电机]

 

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