Iterative Identification for A Class of Closed-loop Systems Based on A Greedy Algorithm

被引：0

作者：

You, Junyao ^{[1
]}

Xu, Huan ^{[1
]}

Liu, Yanjun ^{[1
,2
]}

Chen, Jing ^{[2
]}

机构：

[1] Jiangnan Univ, Sch Internet Things Engn, Wuxi 214122, Peoples R China

[2] Jiangnan Univ, Lab Adv Proc Control Light Ind, Minist Educ, Wuxi 214122, Peoples R China

来源：

PROCEEDINGS OF 2018 IEEE 7TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE (DDCLS) | 2018年

基金：

中国国家自然科学基金;

关键词：

Closed-loop System; Parameter Identification; Time-delay Estimation; Compressive Sampling Matching Pursuit Algorithm; Iteration; TIME-DELAY SYSTEMS; SIGNAL RECOVERY; SPACE;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

A compressive sampling matching pursuit (CoSaMP) iterative algorithm is proposed in this paper to identify parameters and time-delays of a class of closed-loop systems where the forward channel is a CARMA model. Due to the unknown time-delays of both the feedback controller and the controlled plant, a high dimensional identification model with a sparse parameter vector is derived by using an overparameterized method. Then combining the CoSaMP algorithm with the iterative idea, the parameter vector is estimated and the unmeasurable noise items are updated in each iteration. Finally, the parameters of the feedback controller are extracted based on the model equivalence principle and time-delays are estimated according to the sparse characteristic of the parameter vector. The proposed method can simultaneously estimate the parameters and time-delays from a small number of sampled data. The simulation results illustrate that the proposed algorithm is effective.

引用

页码：934 / 938

页数：5

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