Optimized state estimation for nonlinear dynamical networks subject to fading measurements and stochastic coupling strength: an event-triggered communication mechanism

Title:

Optimized state estimation for nonlinear dynamical networks subject to fading measurements and stochastic coupling strength: an event-triggered communication mechanism

Creator:

Jia, Chaoqing , Hu, Jun , Lv, Chongyang , and Shi, Yujing

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:8affaa72-180e-414a-ac67-171857ff47e7
uuid:8affaa72-180e-414a-ac67-171857ff47e7
doi:10.14736/kyb-2020-1-0035

Subject:

event-based communication protocol, fading measurements, stochastic coupling strength, nonlinear dynamical networks, and monotonicity analysis

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

This paper is concerned with the design of event-based state estimation algorithm for nonlinear complex networks with fading measurements and stochastic coupling strength. The event-based communication protocol is employed to save energy and enhance the network transmission efficiency, where the changeable event-triggered threshold is adopted to adjust the data transmission frequency. The phenomenon of fading measurements is described by a series of random variables obeying certain probability distribution. The aim of the paper is to propose a new recursive event-based state estimation strategy such that, for the admissible linearization error, fading measurements and stochastic coupling strength, a minimum upper bound of estimation error covariance is given by designing the estimator gain. Furthermore, the monotonicity relationship between the trace of the upper bound of estimation error covariance and the fading probability is pointed out from the theoretical aspect. Finally, a simulation example is used to show the effectiveness of developed state estimation algorithm.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Coverage:

35-56

Source:

Kybernetika | 2020 Volume:56 | Number:1

Harvested from:

CDK

Metadata only:

false