Comparison of SVSF-KF Adaptive Estimation Algorithms on an Electrohydrostatic Actuator Subject to a Fault

State estimation strategies are vital for obtaining knowledge of a dynamic system's state when faced with limited measurement capability, sensor noise, or uncertain system dynamics. The Kalman filter (KF) is one of the most widely recognized filters and provides the optimal solution for linear...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE sensors journal Ročník 25; číslo 2; s. 2905 - 2920
Hlavní autoři:	Goodman, Jacob, Hilal, Waleed, Gadsden, Stephen A., Eggleton, Charles D.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 15.01.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Actuators Adaptation models Adaptive algorithms Adaptive estimation Adaptive filtering Adaptive systems Algorithms Boundary layers Dynamical systems Estimation estimation theory Fault detection hydrostatic actuator interacting multiple models (IMMs) Kalman filter (KF) Kalman filters Measurement uncertainty Noise Noise measurement Predictor-corrector methods Robustness (mathematics) Sensor phenomena and characterization smooth variable structure filter (SVSF) State estimation Switches System dynamics Uncertainty
ISSN:	1530-437X, 1558-1748
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!