Event-Triggered Discrete-Time Cubature Kalman Filter for Nonlinear Dynamical Systems With Packet Dropout

被引：36

作者：

Kooshkbaghi, Marzieh ^{[1
]}

Marquez, Horacio J. ^{[1
]}

机构：

[1] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 1H9, Canada

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2020年 / 65卷 / 05期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Kalman filters; Sensors; State estimation; Estimation error; Nonlinear systems; Current measurement; Bayes methods; Cubature Kalman Filter (CKF); discrete-time system; event-triggered mechanism; packet dropout; state estimation; STOCHASTIC STABILITY; STATE ESTIMATION;

D O I：

10.1109/TAC.2019.2945286

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a design framework for discrete-time event-triggered cubature Kalman filter for nonlinear dynamic systems over a wireless network with packet dropout. The design ensures that the prediction error covariance is bounded when packet delivery rate has a lower bound. We then show that the estimation error can be guaranteed to be bounded by properly tuning the threshold of the event-triggered mechanism. An example is given to illustrate the filter's performance.

引用

页码：2278 / 2285

页数：8

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