A Novel Identification Method for a Class of Closed-Loop Systems Based on Basis Pursuit De-Noising

被引：5
|
作者：
Chen, Ying [1 ]
Liu, Yanjun [1 ]
Chen, Jing [2 ]
Ma, Junxia [1 ]
机构：
[1] Jiangnan Univ, Sch Internet Things Engn, Key Lab Adv Proc Control Light Ind, Minist Educ, Wuxi 214122, Jiangsu, Peoples R China
[2] Jiangnan Univ, Sch Sci, Wuxi 214122, Jiangsu, Peoples R China
来源：
IEEE ACCESS | 2020年 / 8卷
基金：
中国国家自然科学基金;
关键词：
Closed loop systems; Matching pursuit algorithms; Mathematical model; Sparse matrices; Indexes; Optimization; Noise reduction; Closed-loop system; basis pursuit de-noising; system identification; time-delay estimation; MODEL RECOVERY; RECONSTRUCTION;
D O I：
10.1109/ACCESS.2020.2976862
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a novel method to identify a class of closed-loop systems, in which both the forward channel and the feedback channel have unknown time-delays. Taking into account the time-delays, an overparameterized identification model with a sparse parameter vector is established. Based on the basis pursuit de-noising criterion, the sparse parameter vector is estimated by solving a quadratic programming. The time-delays and the parameters are estimated according to the structure of the parameter estimation vector and the model equivalence principle, respectively. The proposed method is applicable even in the case of a few number of sampled data. The effectiveness of the proposed algorithm is verified by the numerical simulation results.
引用
收藏
页码：99648 / 99654
页数：7
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