Singular Perturbation Margin assessment of linear slowly time-varying systems

Xiaojing Yang; J. Jim Zhu

doi:10.1109/CDC.2012.6426065

Singular Perturbation Margin assessment of linear slowly time-varying systems

Xiaojing Yang^*
, J. Jim Zhu

^*Corresponding author for this work

Ohio University

Research output: Contribution to journal › Conference article › peer-review

3 Scopus citations

Abstract

Singular Perturbation Margin (SPM) is a stability margin for Nonlinear (NL) systems established from the view of the singular perturbation (time-scale separation) parameter. This paper provides two SPM assessment methods: quantitative and qualitative methods for Linear Slowly Time-Varying (LSTV) systems. Quantitative method offers a more accurate estimated SPM than the qualitative method, while the latter is more insightful for the system analysis, and will be helpful for the SPM gauge design in the future. The effectiveness of the two methods is shown by a gain scheduling design example. The results in this paper could also be extended to nonlinear slowly time-varying systems by its linearization thereof.

Original language	English
Article number	6426065
Pages (from-to)	6547-6553
Number of pages	7
Journal	Proceedings of the IEEE Conference on Decision and Control
DOIs	https://doi.org/10.1109/CDC.2012.6426065
State	Published - 2012
Externally published	Yes
Event	51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States Duration: 10 Dec 2012 → 13 Dec 2012

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title = "Singular Perturbation Margin assessment of linear slowly time-varying systems",

abstract = "Singular Perturbation Margin (SPM) is a stability margin for Nonlinear (NL) systems established from the view of the singular perturbation (time-scale separation) parameter. This paper provides two SPM assessment methods: quantitative and qualitative methods for Linear Slowly Time-Varying (LSTV) systems. Quantitative method offers a more accurate estimated SPM than the qualitative method, while the latter is more insightful for the system analysis, and will be helpful for the SPM gauge design in the future. The effectiveness of the two methods is shown by a gain scheduling design example. The results in this paper could also be extended to nonlinear slowly time-varying systems by its linearization thereof.",

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AU - Zhu, J. Jim

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AB - Singular Perturbation Margin (SPM) is a stability margin for Nonlinear (NL) systems established from the view of the singular perturbation (time-scale separation) parameter. This paper provides two SPM assessment methods: quantitative and qualitative methods for Linear Slowly Time-Varying (LSTV) systems. Quantitative method offers a more accurate estimated SPM than the qualitative method, while the latter is more insightful for the system analysis, and will be helpful for the SPM gauge design in the future. The effectiveness of the two methods is shown by a gain scheduling design example. The results in this paper could also be extended to nonlinear slowly time-varying systems by its linearization thereof.

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M1 - 6426065

T2 - 51st IEEE Conference on Decision and Control, CDC 2012

Y2 - 10 December 2012 through 13 December 2012

ER -

Singular Perturbation Margin assessment of linear slowly time-varying systems

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