Optimal robust adaptive observer design for a class of nonlinear systems via an H-infinity approach

Jongchul Jung, Kunsoo Huh, Hosam K. Fathy, Jeffrey L. Stein

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

17 Scopus citations


Existing adaptive observers may suffer parameter estimate drift due to disturbances even if state estimation errors remain small. To avoid such drift in the presence of bounded disturbances, several robust adaptive observers have been introduced providing bounds in state and parameter estimates. However, it is not easy for these observers to manipulate the size of the bounds with the selection of the observer gain. To reduce estimation errors, this paper introduces the H-infinity norm minimization problem in the adaptive observer structure, which minimizes the H-infinity norm between disturbances and estimation errors. The stability condition of the adaptive observer is reformulated as a linear matrix inequality, and the observer gain is optimally chosen by solving the resulting convex optimization problem. The estimation performance is demonstrated through a numerical example.

Original languageEnglish (US)
Title of host publicationProceedings of the 2006 American Control Conference
Number of pages6
StatePublished - 2006
Event2006 American Control Conference - Minneapolis, MN, United States
Duration: Jun 14 2006Jun 16 2006

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Other2006 American Control Conference
Country/TerritoryUnited States
CityMinneapolis, MN

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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