个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职:Professor at the Institute of Advanced Measurement & Control Technology
其他任职:先进检测与控制技术研究所所长
性别:男
毕业院校:上海交通大学
学位:博士
所在单位:控制科学与工程学院
学科:控制理论与控制工程. 化学工程
办公地点:大连理工大学控制科学与工程学院先进检测与控制技术研究所
大连市凌工路2号大连理工大学海山楼A座724室
联系方式:Tel:(0411)84706465 实验室网站:http://act.dlut.edu.cn/
电子邮箱:tliu@dlut.edu.cn
Subspace model identification under load disturbance with unknown transient and periodic dynamics
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论文类型:期刊论文
发表时间:2020-01-01
发表刊物:JOURNAL OF PROCESS CONTROL
收录刊物:EI、SCIE
卷号:85
页面范围:100-111
ISSN号:0959-1524
关键字:Subspace identification; load disturbance; deterministic system response; oblique projection; consistent estimation
摘要:To overcome the influence from load disturbance with unknown transient and periodic dynamics, as often encountered when performing identification tests in engineering applications, a bias-eliminated subspace model identification method is proposed to realize consistent estimation, which can be used for both open- and closed-loop systems. By decomposing the output response into disturbed and undisturbed components, an oblique projection is subtly introduced to eliminate the disturbance and noise impact so as to obtain unbiased estimation on the deterministic system state matrices, while the disturbance response dynamics could be estimated. In particular, a specific algorithm based on minimizing the output prediction error is given to find out the disturbance period if exists, such that the disturbance effect can be eliminated by the above projection regardless of the disturbance waveform and magnitude. A shift-invariant approach is then given to retrieve the deterministic state matrices. Consistent estimation on the deterministic system matrices is analyzed with a proof. A benmark example from the literature and an industrial injection molding process are used to demonstrate the effectiveness and merit of the proposed method. (C) 2019 Published by Elsevier Ltd.