Lyapunov-based nonlinear observer design for stochastic systems

E. Yaz; A. Azemi

doi:10.1109/cdc.1990.203583

Lyapunov-based nonlinear observer design for stochastic systems

E. Yaz, A. Azemi

Penn State Brandywine

Research output: Contribution to journal › Conference article › peer-review

3 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 language	English (US)
Pages (from-to)	218-219
Number of pages	2
Journal	Proceedings of the IEEE Conference on Decision and Control
Volume	1
DOIs	https://doi.org/10.1109/cdc.1990.203583
State	Published - 1990
Event	Proceedings of the 29th IEEE Conference on Decision and Control Part 6 (of 6) - Honolulu, HI, USA Duration: Dec 5 1990 → Dec 7 1990

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

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10.1109/cdc.1990.203583

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title = "Lyapunov-based nonlinear observer design for stochastic systems",

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.",

author = "E. Yaz and A. Azemi",

year = "1990",

doi = "10.1109/cdc.1990.203583",

language = "English (US)",

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journal = "Proceedings of the IEEE Conference on Decision and Control",

issn = "0191-2216",

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note = "Proceedings of the 29th IEEE Conference on Decision and Control Part 6 (of 6) ; Conference date: 05-12-1990 Through 07-12-1990",

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AU - Azemi, A.

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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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M3 - Conference article

AN - SCOPUS:0025547492

SN - 0191-2216

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SP - 218

EP - 219

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

T2 - Proceedings of the 29th IEEE Conference on Decision and Control Part 6 (of 6)

Y2 - 5 December 1990 through 7 December 1990

ER -

Lyapunov-based nonlinear observer design for stochastic systems

Abstract

All Science Journal Classification (ASJC) codes

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