Data-driven MPC of descriptor systems: A case study for power networks

被引：6

作者：

Schmitz, Philipp ^{[1
]}

Engelmann, Alexander ^{[2
]}

Faulwasser, Timm ^{[2
]}

Worthmann, Karl ^{[1
]}

机构：

[1] Tech Univ Ilmenau, Inst Math, Optimizat Based Control, Ilmenau, Germany

[2] TU Dortmund Univ, Inst Energy Syst Energy Efficiency & Energy Econ, Dortmund, Germany

来源：

IFAC PAPERSONLINE | 2022年 / 55卷 / 30期

关键词：

Data-driven control; descriptor systems; MPC; Willems' fundamental lemma; optimal control; power-swing equations; power systems; AUTOMATIC-GENERATION CONTROL; FREQUENCY CONTROL; STABILITY; MODEL; MICROGRIDS;

D O I：

10.1016/j.ifacol.2022.11.079

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Recently, data-driven predictive control of linear systems has received wide-spread research attention. It hinges on the fundamental lemma by Willems et al. In a previous paper, we have shown how this framework can be applied to predictive control of linear time-invariant descriptor systems. In the present paper, we present a case study wherein we apply data-driven predictive control to a discrete-time descriptor model obtained by discretization of the power-swing equations for a nine-bus system. Our results show the efficacy of the proposed control scheme and they underpin the prospect of the data-driven framework for control of descriptor systems. Copyright (C) 2022 The Authors.

引用

页码：359 / 364

页数：6

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