Data-Driven Dissipativity Analysis of Linear Parameter-Varying Systems

被引：0

作者：

Verhoek C. ^{[1
]}

Berberich J. ^{[2
]}

Haesaert S. ^{[1
]}

Allgower F. ^{[2
]}

Toth R. ^{[1
]}

机构：

[1] Control Systems Group, Eindhoven University of Technology

[2] Institute for Systems Theory and Automatic Control, University of Stuttgart

来源：

IEEE Trans Autom Control | 2024年 / 12卷 / 8603-8616期

关键词：

Analytical models; Behavioral systems; data-driven control; dissipativity analysis; linear parameter-varying systems; Linear systems; Nonlinear systems; Processor scheduling; Time-varying systems; Trajectory; Vectors;

D O I：

10.1109/TAC.2024.3417855

中图分类号：

学科分类号：

摘要：

We derive direct data-driven dissipativity analysis methods for Linear Parameter-Varying (LPV) systems using a single sequence of input-scheduling-output data. By means of constructing a semi-definite program subject to linear matrix inequality constraints based on this <italic>data-dictionary</italic>, direct data-driven verification of <inline-formula><tex-math notation="LaTeX">$(Q,S,R)$</tex-math></inline-formula>-type of dissipativity properties of the data-generating LPV system is achieved. Multiple implementation methods are proposed to achieve efficient computational properties and to even exploit structural information on the scheduling, e.g., rate bounds. The effectiveness and trade-offs of the proposed methodologies are shown in simulation studies of academic and physically realistic examples. IEEE

引用

页码：1 / 14

页数：13

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