Results 81 to 90 of about 7,896 (220)

An adaptive square-root unscented Kalman filter for underwater Vehicle navigation [PDF]

open access: yes, 2014
In order to increase the approximation accuracy of the state estimate of nonlinear systems and to guarantee numerical stability of the unscented Kalman filter (UKF), a novel adaptive square-root unscented Kalman filter (ASRUKF) based on modified Sage ...
Liu KZ(刘开周)   +2 more
core  

Unscented Kalman Filtering for Attitude Determination Using MEMS Sensors [PDF]

open access: yes, 2013
This paper presents the results of a quaternion-based unscented Kalman filtering for attitude estimation using low cost MEMS sensors. The unscented Kalman filter uses the pitch and roll angles computed from gravity force decomposition as the measurement ...
Shiau, Jaw-Kuen; Wang, I-Chiang
core   +1 more source

UKF based estimation approach for DVR control to compensate voltage swell in distribution systems

open access: yesAin Shams Engineering Journal, 2018
The Dynamic Voltage Restorer (DVR) is identified as the best solution for mitigation of voltage sag and swell related problems in the much taped distribution system. The compensation performance of the DVR very much depends on its control algorithm.
P. SasiKiran, T. Gowri Manohar
doaj   +1 more source

Adaptive Neural Unscented Kalman Filter

open access: yesIEEE Transactions on Intelligent Vehicles
eight pages, ten ...
Amit Levy 0002, Itzik Klein
openaire   +2 more sources

State of Charge Estimation of EV Secondary Battery Pack Using Hybrid Hedge Feedforward Feedback‐Based Gated Recurrent Unit to Extend Lifespan

open access: yesBattery Energy, Volume 5, Issue 2, March 2026.
SOC estimation is performed using a newly developed online HFF‐GRU method. Improves charge balancing among battery cells, leading to a substantial increase in the battery pack's lifespan. ABSTRACT Accurate estimation of state of charge (SoC) and maintaining balanced charge levels across secondary battery cells are crucial in battery management systems (
Md Ohirul Qays   +4 more
wiley   +1 more source

Tracking control of underactuated surface ships: Using unscented kalman filter to estimate the uncertain parameters [PDF]

open access: yes, 2007
This paper proposes an unscented Kalman filter (UKF) based tracldng controller to force underactuated nonlinear autonomous ships to follow a reference path under constant disturbances induced by wave, wind and ocean-current. The controller development is
Song Q(宋崎)   +2 more
core  

Integrating the Utkin observer with the unscented Kalman filter [PDF]

open access: yes, 2008
This paper describes the integration of an Utkin observer with the unscented Kalman filter, investigates the performance of the combined observer, termed the unscented Utkin observer, and compares it with an unscented Kalman filter.
Becerra, V. M.   +5 more
core   +1 more source

Accurate State of Charge Estimation in Lithium‐Ion Batteries by Second‐Order Sliding Mode Observer

open access: yesBattery Energy, Volume 5, Issue 2, March 2026.
A finite‐time second‐order sliding mode observer (SO‐SMO) is proposed for accurate and robust state‐of‐charge estimation in lithium‐ion batteries, achieving fast convergence, chattering elimination, and superior estimation accuracy compared to conventional methods, making it ideal for real‐time battery management applications in electric and hybrid ...
Mohammad Asadi   +5 more
wiley   +1 more source

Tracking Control of Unmanned Trimaran Surface Vehicle: Using Adaptive Unscented Kalman Filter to Estimate the Uncertain Parameters [PDF]

open access: yes, 2008
This paper proposes an Adaptive unscented Kalman filter (UKF) based tracking controller to force underactuated nonlinear autonomous ships to follow a reference path under constant disturbances induced by wave, wind and ocean-current.
Jianda Han   +3 more
core   +1 more source

Machine learning of radial basis function neural network based on Kalman filter: Introduction [PDF]

open access: yesTehnika, 2014
This paper analyzes machine learning of radial basis function neural network based on Kalman filtering. Three algorithms are derived: linearized Kalman filter, linearized information filter and unscented Kalman filter.
Vuković Najdan L., Miljković Zoran Đ.
doaj   +1 more source

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