Data-driven Estimation of Finite-time Controllability Gramians

被引：0

作者：

Banno, Ikumi ^{[1
]}

Azuma, Shun-Ichi ^{[1
]}

Ariizumi, Ryo ^{[1
]}

Asai, Toru ^{[1
]}

Imura, Jun-Ichi ^{[2
]}

机构：

[1] Nagoya Univ, Grad Sch Engn, Aichi, Japan

[2] Tokyo Inst Technol, Grad Sch Engn, Tokyo, Japan

来源：

2021 60TH ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS OF JAPAN (SICE) | 2021年

关键词：

Data-driven control; estimation; controllability Gramian;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In networked control, one of the fundamental problems is to select control nodes. When the plant is unknown, the data-driven approach plays a key role in the problem. This paper presents a data-driven estimation of finite-time controllability Gramians of unknown linear systems. First, we develop a method for calculating a solution to a class of Lyapunov equations associated with the system by using the state trajectories. Based on this result, we propose a data-driven estimation method of the finite-time controllability Gramians. The proposed method is demonstrated through numerical simulation.

引用

页码：666 / 670

页数：5

共 7 条

[1]

Banno I., 2021, P 60 IEEE C DECISION

[2] Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers [J].