Results 51 to 60 of about 9,303 (171)

Data-Driven Intrusion Detection in Vehicles: Integrating Unscented Kalman Filter (UKF) with Machine Learning

Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics
Accepted in Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-717-7, SciTePress, pages 714-723.
Bian, Shuhao, Farsi, Milad, Azad, Nasser L., Hobbs, Chris   +3 more
openaire   +2 more sources

A Robust Algorithm for State-of-Charge Estimation under Model Uncertainty and Voltage Sensor Bias

Energies, 2022
Accurate estimation of the state of charge (SOC) of zinc–nickel single-flow batteries (ZNBs) is an important problem in battery management systems (BMSs).
Yang Guo, Ziguang Lu
doaj   +1 more source

Sparsity-Based Kalman Filters for Data Assimilation [PDF]

, 2018
Several variations of the Kalman filter algorithm, such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), are widely used in science and engineering applications.
Kang, Wei, Xu, Liang
core   +1 more source

A State Estimation of Dynamic Parameters of Electric Drive Articulated Vehicles Based on the Forgetting Factor of Unscented Kalman Filter with Singular Value Decomposition

Actuators
In this paper, a state estimation method of distributed electric drive articulated vehicle dynamics parameters based on the forgetting factor unscented Kalman filter with singular value decomposition (SVD-UKF) is proposed.
Tianlong Lei, Mingming Hou, Liaoyuan Li, Haohua Cao   +3 more
doaj   +1 more source

UKF-Based Parameter Estimation and Identification for Permanent Magnet Synchronous Motor

Frontiers in Energy Research, 2022
The accuracy of rotor position estimation determines the performance of the sensorless control system of a permanent magnet synchronous motor. In order to realize the accurate control of rotor position and speed, it is necessary to identify the motor ...
Zhiwei Wang, Xin Liu, Wenzhuo Wang, Yunling Lv, Bo Yuan, Wujing Li, Qiufang Li, Shijie Wang, Qianchang Chen, Yi Zhang   +9 more
doaj   +1 more source

Automated weighing by sequential inference in dynamic environments

, 2015
We demonstrate sequential mass inference of a suspended bag of milk powder from simulated measurements of the vertical force component at the pivot while the bag is being filled.
Martin, A. D., Molteno, T. C. A.
core   +1 more source

Study of the Effectiveness of Different Kalman Filtering Methods and Smoothers in Object Tracking Based on Simulation Tests

Reports on Geodesy and Geoinformatics, 2015
In navigation practice, there are various navigational architecture and integration strategies of measuring instruments that affect the choice of the Kalman filtering algorithm.
Malinowski Marcin, Kwiecień Janusz
doaj   +1 more source

Robust Filtering and Smoothing with Gaussian Processes

, 2012
We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models.
,, Deisenroth, MP, Hanebeck, UD, Huber, MF, Rasmussen, CE, Turner, RD   +5 more
core   +1 more source

Inference in Nonlinear Systems with Unscented Kalman Filters [PDF]

, 2016
An increasing number of scientific disciplines, most notably the life sciences and health care, have become more quantitative, describing complex systems with coupled nonlinear di↵erential equations.
Giurghita, Diana, Husmeier, Dirk
core  

A New Approach to Linear/Nonlinear Distributed Fusion Estimation Problem

, 2018
Disturbance noises are always bounded in a practical system, while fusion estimation is to best utilize multiple sensor data containing noises for the purpose of estimating a quantity--a parameter or process.
Chen, Bo, Ho, Daniel W. C., Hu, Guoqiang, Yu, Li   +3 more
core   +1 more source