Lyapunov-based nonlinear observer design for stochastic systems

E. Yaz, Asad Azemi

Research output: Contribution to journalConference article

2 Citations (Scopus)

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

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Nonlinear Observer
Observer Design
Stochastic systems
State estimation
Stochastic Systems
Error analysis
Lyapunov
Nonlinear Stochastic Systems
Optimization Theory
Stochastic Stability
State Estimation
Estimation Error
Mean Square
Design Methodology
Continuous Time
Observer
Rate of Convergence
Filter
Model

All Science Journal Classification (ASJC) codes

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

Cite this

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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.",
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Lyapunov-based nonlinear observer design for stochastic systems. / Yaz, E.; Azemi, Asad.

In: Proceedings of the IEEE Conference on Decision and Control, Vol. 1, 01.12.1990, p. 218-219.

Research output: Contribution to journalConference article

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T1 - Lyapunov-based nonlinear observer design for stochastic systems

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AU - Azemi, Asad

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N2 - 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.

AB - 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.

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