Lyapunov-based nonlinear observer design for stochastic systems

E. Yaz, Asad Azemi

Research output: Contribution to journalConference article

2 Scopus citations

Abstract

An observer design methodology which is applicable to more general nonlinear stochastic system models is given. The method relies not on the optimization theory but on Lyapunov-type stochastic stability results which can guarantee a mean square exponential rate of convergence for the estimation error. It is proved that discrete- and continuous-time state estimation is possible using the method. An example is given to illustrate the performance of this observer relative to some of the most commonly used filters in this field.

Original languageEnglish (US)
Pages (from-to)218-219
Number of pages2
JournalProceedings of the IEEE Conference on Decision and Control
Volume1
StatePublished - Dec 1 1990
EventProceedings of the 29th IEEE Conference on Decision and Control Part 6 (of 6) - Honolulu, HI, USA
Duration: Dec 5 1990Dec 7 1990

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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