Robustness Analysis of Descriptor Systems with Parameter Uncertainties

Chunyu Yang, Qingling Zhang, Fuzhen Zhang, Zheng Zhou

Research output: Contribution to journalArticlepeer-review

Abstract

This paper investigates the problem of robustness analysis for descriptor systems with parameter uncertainties in both the derivative and state matrices. Using a parameter dependent Lyapunov function we derive a linear matrix inequality (LMI) based sufficient condition for the admissibility of the system. Unlike the existing results, our criterion has no restriction on the rank of the derivative matrix. Further, we use the obtained method to study interval descriptor systems and multi-parameter singular perturbed systems. The proposed approaches overcome some drawbacks of the existing results. Finally, we present two numerical examples to show the effectiveness of the main results. © ICROS, KIEE and Springer 2010.
Original languageAmerican English
Pages (from-to)204-209
Number of pages6
JournalInternational Journal of Control, Automation, and Systems
Volume8
Issue number2
DOIs
StatePublished - Apr 1 2010

Funding

Manuscript received July 12, 2008; revised April 4, 2009; accepted September 1, 2009. Recommended by Editorial Board member Poo Gyeon Park under the direction of Editor Jae Weon Choi. This work was supported by the Natural Science Foundation of China (60904009), Fundamental Research Funds for the Central Universities of China (N090408001), Funds for Creative Research Groups of China (60521003) and National Basic Research Program of China (2009CB320601).

FundersFunder number
Funds for Creative Research Groups of China60521003
National Natural Science Foundation of China60904009
National Basic Research Program of China (973 Program)2009CB320601
Fundamental Research Funds for the Central UniversitiesN090408001

    ASJC Scopus Subject Areas

    • Control and Systems Engineering
    • Computer Science Applications

    Keywords

    • Descriptor systems
    • Linear matrix inequality (LMI)
    • Parameter uncertainties
    • Robustness

    Disciplines

    • Mathematics

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