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

2020 ◽  
Vol 65 (5) ◽  
pp. 2278-2285
Author(s):  
Marzieh Kooshkbaghi ◽  
Horacio J. Marquez
Keyword(s):  
Kalman Filter ◽  
Dynamical Systems ◽  
Discrete Time ◽  
Nonlinear Dynamical Systems ◽  
Packet Dropout ◽  
Nonlinear Dynamical ◽  
Cubature Kalman Filter ◽  
Event Triggered

THE UNSCENTED KALMAN FILTER, A POWERFUL TOOL FOR DATA ANALYSIS

2004 ◽  
Vol 14 (06) ◽  
pp. 2093-2105 ◽  
Author(s):  
A. SITZ ◽  
U. SCHWARZ ◽  
J. KURTHS
Keyword(s):  
Kalman Filter ◽  
Data Analysis ◽  
Dynamical Systems ◽  
Unscented Kalman Filter ◽  
Nonlinear Dynamical Systems ◽  
Simultaneous Estimation ◽  
Bayesian Filter ◽  
Nonlinear Dynamical

We present a derivation of the unscented Kalman filter (UKF) as an approximation to the optimal Bayesian filter equations. The potentials of the UKF are then demonstrated for the problem of simultaneous estimation of states and parameters from noise corrupted data of nonlinear dynamical systems. The UKF even works for the chaotic Chua system which includes nondifferentiable terms.

Sign in / Sign up

Export Citation Format

Share Document