摘要
复杂工业化中大部分的被控对象都具有非线性的特点,不易建立模型。数据驱动控制可以解决这一难题,数据驱动最大的优点是不需要知道被控系统精准的模型,根据输入输出的数据来进行模型的辨识与优化。对数据驱动的无模型自适应控制(Model Free Adaptive Control,MFAC)进行了系统研究,通过PCS7编程,使用SMPT1000仿真平台结合MATLAB仿真验证此方法的优越性。并与传统的PID控制进行对比。研究结果表明:MFAC控制较传统PID控制,系统的动态性能指标更好。
Most of the controlled objects in complex industrialization have nonlinear characteristics and their models are not easy to establish.Data-driven control can solve this problem.The biggest advantage of data-driven is that the precise model of the controlled system is not necessary,which can be identified and optimized by the input and output data.Modeless adaptive control(MFAC)in data-driven control was proposed,and the advantages of this method were verified by PCS7 programming,smpt1000 simulation platform and MATLAB simulation.Compared with the traditional PID control.The results show that the dynamic performance of the MFAC is better than that of the traditional PID control,and which is effective for industrial production control.
作者
曾凯
钱俊磊
徐越
刘博
安江伟
ZENG Kai;QIAN Jun-lei;XU Yue;LIU Bo;AN Jiang-wei(College of Electrical Engineering,North China University of Science and Technology,Tangshan Hebei 063210,China;School of Electric and Information Engineering,Guangxi University of Science and Technology,Liuzhou Guangxi 545006,China;Xingheng Detection Co.,Ltd.Tangshan Hebei 063020,China;Tangshan Anode Automation Co.,Ltd.Tangshan Hebei 063020,China)
出处
《华北理工大学学报（自然科学版）》
CAS
2021年第4期60-66,126,共8页
Journal of North China University of Science and Technology：Natural Science Edition
基金
河北省省属高等学校基本科研业务费研究项目(JYG2020004),河北省钢铁联合基金项目(ZL201710693874.3)。
