Guaranteed cost state estimation of stochastic uncertain systems with slope bounded nonlinearities via the use of dynamic multipliers

Hua Ouyang, Ian R. Petersen

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

2 Citations (Scopus)

Abstract

This paper presents a new approach to robust nonlinear state estimation based on the use of Integral Quadratic Constraints and minimax LQG control. The approach involves a class of state estimators which include copies of the slope bounded nonlinearities occurring in the plant. Integral Quadratic Constraints and dynamic multipliers are introduced to exploit these repeated nonlinearities. The linear part of the state estimator is synthesized using minimax LQG control theory and this leads to a nonlinear state estimator which gives an upper bound on the closed loop value of a quadratic cost functional.

Original languageEnglish
Title of host publicationProceedings of the 46th IEEE Conference on Decision and Control 2007, CDC
Pages5557-5563
Number of pages7
DOIs
Publication statusPublished - Dec 1 2007
Event46th IEEE Conference on Decision and Control 2007, CDC - New Orleans, LA, United States
Duration: Dec 12 2007Dec 14 2007

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other46th IEEE Conference on Decision and Control 2007, CDC
CountryUnited States
CityNew Orleans, LA
Period12/12/0712/14/07

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization

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    Ouyang, H., & Petersen, I. R. (2007). Guaranteed cost state estimation of stochastic uncertain systems with slope bounded nonlinearities via the use of dynamic multipliers. In Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC (pp. 5557-5563). [4434425] (Proceedings of the IEEE Conference on Decision and Control). https://doi.org/10.1109/CDC.2007.4434425