Characteristic Modeling Approach for High-Order Linear Dynamical Systems

被引：2
|
作者：
Chen, Lei [1 ]
Yu, Xinghuo [2 ]
Sun, Changyin [3 ]
机构：
[1] Beihang Univ, Beijing Adv Innovat Ctr Big Data & Brain Comp, Sch Automat Sci & Elect Engn, State Key Lab Software Dev Environm, Beijing 100191, Peoples R China
[2] RMIT Univ, Sch Engn, Melbourne, Vic 3001, Australia
[3] Southeast Univ, Sch Automat, Nanjing 210096, Peoples R China
来源：
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2021年 / 51卷 / 09期
基金：
澳大利亚研究理事会; 中国国家自然科学基金;
关键词：
Mathematical model; Dynamical systems; Linear systems; Sun; Feature extraction; Automation; Adaptation models; Compression; linear systems; mathematical modeling; order-reduction; DESIGN; REDUCTION;
D O I：
10.1109/TSMC.2019.2956484
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 article presents a full mathematical proof of the characteristic modeling approach for high-order linear dynamical systems. It explores the nature of the characteristic model in rigorous mathematical forms, also showing why and how the high-order dynamics can be compressed into the lower-order characteristic model. The relationships between high-order linear continuous dynamical systems, discrete-time characteristic model coefficients, and sampling-time intervals are investigated.
引用
收藏
页码：5405 / 5413
页数：9
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