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

被引：29
|
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
收藏
页码：2278 / 2285
页数：8
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