Abstract | ||
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Dissipativity analysis is an important tool for the analysis of the dynamic response of systems of Ordinary Differential Equations to structural and parametric perturbations. In order to certify dissipativity, semi-definite programming is commonly used for the computation of storage functions of polynomial systems, but is currently not a practical solution for large-scale systems. This paper formulates the computation of a class of structured storage functions that exploit the structure of systems that can be decomposed into cascades. Structured storage functions allow the decomposition of the semi-definite programs used to prove dissipativity, thereby reducing the computational cost of SOS programming and making its application to large-scale systems more practical. Thus structured storage functions deliver additional speed and flexibility to the dissipativity approach to parametric and structural sensitivity analysis. |
Year | DOI | Venue |
---|---|---|
2014 | 10.1109/CDC.2014.7040247 | Decision and Control |
Keywords | Field | DocType |
cascade systems,control system analysis,differential equations,mathematical programming,SOS programming,cascaded systems,dissipativity analysis,large-scale systems,ordinary differential equations,polynomial system storage functions,semidefinite programming,structural sensitivity analysis,structured storage functions | Mathematical optimization,Polynomial,Ordinary differential equation,Computer science,Control theory,Exploit,Parametric statistics,Computation | Conference |
ISSN | Citations | PageRank |
0743-1546 | 1 | 0.63 |
References | Authors | |
6 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Thomas P. Prescott | 1 | 8 | 2.60 |
Antonis Papachristodoulou | 2 | 990 | 90.01 |