Output-feedback sampled-data control for uncertain nonlinear system

Hwa Chang Sung, Jin Bae Park, Jong Seon Kim, Young Hoon Joo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we concern an intelligent digital redesign(IDR) method for a fuzzy observer-based output-feedback control system which includes parametric uncertainties. The term IDR is to convert an existing analog control into an equivalent digital counterpart via state-matching. The considered IDR problem is viewed as convex minimization problem of the norm distances between linear operators to be matched and its constructive condition is formulated in terms of linear matrix inequalities (LMIs). The main features of the proposed method are that the state estimation error in the plant dynamics is considered in the IDR condition that plays a crucial role in the performance improvement; the uncertainties in the plant dynamics is shown in the IDR condition by virtue of the bilinear and inverse-bilinear approximation method; finally, the stability property is preserved by the proposed IDR method.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Fuzzy Systems - Proceedings
Pages2109-2113
Number of pages5
DOIs
Publication statusPublished - 2009 Dec 10
Event2009 IEEE International Conference on Fuzzy Systems - Jeju Island, Korea, Republic of
Duration: 2009 Aug 202009 Aug 24

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Other

Other2009 IEEE International Conference on Fuzzy Systems
CountryKorea, Republic of
CityJeju Island
Period09/8/2009/8/24

Fingerprint

Digital Redesign
Sampled-data Control
Uncertain Nonlinear Systems
Output Feedback
Feedback Control
Nonlinear systems
Feedback
State estimation
Linear matrix inequalities
Feedback control
Mathematical operators
Control systems
Fuzzy Observer
Convex Minimization
Output Feedback Control
Parametric Uncertainty
Feedback Systems
State Estimation
Estimation Error
Approximation Methods

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

Cite this

Sung, H. C., Park, J. B., Kim, J. S., & Joo, Y. H. (2009). Output-feedback sampled-data control for uncertain nonlinear system. In 2009 IEEE International Conference on Fuzzy Systems - Proceedings (pp. 2109-2113). [5277163] (IEEE International Conference on Fuzzy Systems). https://doi.org/10.1109/FUZZY.2009.5277163
Sung, Hwa Chang ; Park, Jin Bae ; Kim, Jong Seon ; Joo, Young Hoon. / Output-feedback sampled-data control for uncertain nonlinear system. 2009 IEEE International Conference on Fuzzy Systems - Proceedings. 2009. pp. 2109-2113 (IEEE International Conference on Fuzzy Systems).
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Sung, HC, Park, JB, Kim, JS & Joo, YH 2009, Output-feedback sampled-data control for uncertain nonlinear system. in 2009 IEEE International Conference on Fuzzy Systems - Proceedings., 5277163, IEEE International Conference on Fuzzy Systems, pp. 2109-2113, 2009 IEEE International Conference on Fuzzy Systems, Jeju Island, Korea, Republic of, 09/8/20. https://doi.org/10.1109/FUZZY.2009.5277163

Output-feedback sampled-data control for uncertain nonlinear system. / Sung, Hwa Chang; Park, Jin Bae; Kim, Jong Seon; Joo, Young Hoon.

2009 IEEE International Conference on Fuzzy Systems - Proceedings. 2009. p. 2109-2113 5277163 (IEEE International Conference on Fuzzy Systems).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - In this paper, we concern an intelligent digital redesign(IDR) method for a fuzzy observer-based output-feedback control system which includes parametric uncertainties. The term IDR is to convert an existing analog control into an equivalent digital counterpart via state-matching. The considered IDR problem is viewed as convex minimization problem of the norm distances between linear operators to be matched and its constructive condition is formulated in terms of linear matrix inequalities (LMIs). The main features of the proposed method are that the state estimation error in the plant dynamics is considered in the IDR condition that plays a crucial role in the performance improvement; the uncertainties in the plant dynamics is shown in the IDR condition by virtue of the bilinear and inverse-bilinear approximation method; finally, the stability property is preserved by the proposed IDR method.

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Sung HC, Park JB, Kim JS, Joo YH. Output-feedback sampled-data control for uncertain nonlinear system. In 2009 IEEE International Conference on Fuzzy Systems - Proceedings. 2009. p. 2109-2113. 5277163. (IEEE International Conference on Fuzzy Systems). https://doi.org/10.1109/FUZZY.2009.5277163