A Novel Networked Online Recursive Identification Method for Multivariable Systems With Incomplete Measurement Information

被引：16

作者：

Du, Dajun ^{[1
]}

Chen, Rui ^{[1
]}

Fei, Minrui ^{[1
]}

Li, Kang ^{[2
]}

机构：

[1] Shanghai Univ, Sch Mech Engn & Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China

[2] Queens Univ Belfast, Sch Elect Elect Engn & Comp Sci, Belfast BT9 5AH, Antrim, North Ireland

来源：

IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS | 2017年 / 3卷 / 04期

基金：

美国国家科学基金会; 英国工程与自然科学研究理事会;

关键词：

Auxiliary model strategy; bernoulli distribution; convergence rate; incomplete information; networked environment; online recursive identification algorithm; PARAMETER-ESTIMATION; AUXILIARY MODEL; SCARCE MEASUREMENTS; CONVERGENCE ANALYSIS; SENSOR NETWORKS; DELAYS; CONSTRAINTS; ENVIRONMENT; ALGORITHMS; DESIGN;

D O I：

10.1109/TSIPN.2017.2662621

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Network-based identification of multivariable systems plays a key role in future smart manufacturing systems in achieving the goals of industry 4.0. The incomplete information caused by network traffic congestion or cyber attacks in the networked environment will inevitably deteriorate the performance of system identification, and in the extreme cases, it will cause nonconvergence of the identifier. Unlike the traditional recursive least-squares algorithms based on the complete data, this paper investigates a novel networked online recursive identification method for multivariable systems with incomplete information. In this new algorithm, the characteristics of data packet dropouts are first formulated as a Bernoulli process, and the lost data are compensated by an auxiliary model. A new information set including networked parameters is then constructed, and the corresponding networked online identification algorithm for multivariable systems is proposed. The proposed algorithm can overcome the negative effect of data packet losses on the identification performance and can be updated recursively. Furthermore, using the Lyapunov and martingale-methods, the convergence rate of the proposed algorithm as well as its computational complexity is analyzed in detail. Simulation examples confirm the feasibility and efficiency of the proposed method.

引用

页码：744 / 759

页数：16

共 48 条

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