Results 131 to 140 of about 1,983 (163)

Real time SOC estimation for Li-ion batteries in Electric vehicles using UKBF with online parameter identification. [PDF]

Sci Rep
Nachimuthu S, Alsaif F, Devarajan G, Vairavasundaram I.   +3 more
europepmc   +1 more source

State estimation in an islanded hybrid solar-wind DC microgrid using Unscented Kalman Filter. [PDF]

Heliyon
HajiHeydari Varnoosfaderani N, Khorsandi A.   +1 more
europepmc   +1 more source

Variational adaptive Gaussian approximation filter for nonlinear systems with generalized unknown disturbances. [PDF]

iScience
Qin Y, Lv J, Li S, Hou Y.
europepmc   +1 more source

Local Linear Wavelet Neural Network-Based Unscented Kalman Filter for Vehicle Collision Estimate Warning System and Ensuring Stable Vehicle-to-Infrastructure Communication. [PDF]

Appl Bionics Biomech
Lema YK, Mishra S, Gelmecha DJ.
europepmc   +1 more source

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A Scaled Spherical Simplex Filter (S3F) with a decreased n + 2 sigma points set size and equivalent 2n + 1 Unscented Kalman Filter (UKF) accuracy

Mechanical Systems and Signal Processing, 2022
Abstract The computational efficiency of a sampling based nonlinear Kalman filtering process is mainly conditional on the number of sigma/sample points required by the filter at each time step to effectively quantify statistical properties of related states and parameters.
Konstantinos G Papakonstantinou
exaly   +2 more sources

Adaptive unscented Kalman filter (UKF) for acoustic emission (AE) source localization in noisy environment

Proceedings of SPIE, 2013
ABSTRACT This paper proposes an adaptive Unscented Kalman Filter (UKF) algorithm for Acoustic Emission (AE) source localization in plate-like structures in noisy environments. Over all, the proposed approach consists of four main stages: 1) feature extraction, 2) sensor selection based on a binary hypothesis testing, 3) sensor weighting based on a well-
Salvatore Salamone, Alireza Farhidzadeh   +1 more
exaly   +2 more sources

GP-UKF: Unscented kalman filters with Gaussian process prediction and observation models

2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007
This paper considers the use of non-parametric system models for sequential state estimation. In particular, motion and observation models are learned from training examples using Gaussian process (GP) regression. The state estimator is an unscented Kalman filter (UKF). The resulting GP-UKF algorithm has a number of advantages over standard (parametric)
Jonathan Ko, Daniel J. Klein, Dieter Fox, Dirk Hähnel   +3 more
openaire   +1 more source

The unscented Kalman filter (UKF)-based algorithm for regional frequency analysis of extreme rainfall events in a nonstationary environment

Journal of Hydrology, 2021
Abstract In regional frequency analysis, extreme rainfall patterns in a nonstationary environment are characterized by the time-dependent regional growth curves, in which location and scale parameters are the weighted values of at-site estimates from the sites within a homogeneous group.
openaire   +1 more source

Estimation of vehicle yaw rate and lateral motion for dynamic stability control using unscented Kalman filtering (UKF) approach

Michael Faraday IET International Summit 2015, 2015
The increasing demand for passenger safety and comfort has inspired to develop technologically sophisticated automobiles that provide improved vehicle handling. In automotive industry, current focus is on the development of active safety systems, which assist the driver in order to avoid critical situations. Unfortunately, some fundamental states which
S. Sen, A. Sutradhar, S. Chakraborty
openaire   +1 more source