Zobrazeno 1 - 10
of 14
pro vyhledávání: '"and Mohammad Alshabi"'
Publikováno v:
IEEE Access, Vol 12, Pp 178552-178565 (2024)
This work develops a novel formulation of the lattice Kalman filter (LKF) for enhanced robustness. This novel approach initially integrates the concept of sliding innovation to refine the measurement update phase of the LKF, ensuring that the filter
Externí odkaz:
https://doaj.org/article/91dfe12ab71c4cd4b5ee0b790f11a028
Publikováno v:
IEEE Open Journal of Instrumentation and Measurement, Vol 3, Pp 1-12 (2024)
This article proposes an enhanced fusion technique to improve the accuracy of the state estimation of a navigational system. The smooth variable structure filter (SVSF) is examined to estimate the system’s state under model uncertainty. Its combina
Externí odkaz:
https://doaj.org/article/8825c32b2de144e08e85e2bae6635dfd
Autor:
Abolfazl Rahimnejad, Javad Enayati, Luigi Vanfretti, Stephen Andrew Gadsden, Mohammad AlShabi
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 4, Pp 410-423 (2023)
This article introduces the Sliding Innovation Lattice Filter (SILF), a robust extension of the Lattice Kalman Filter (LKF) that leverages sliding mode theory. SILF incorporates a sliding boundary layer in the measurement update formulation, enabling
Externí odkaz:
https://doaj.org/article/fb00183fa5004f009df0c42a872f5cae
Publikováno v:
Sensors, Vol 24, Iss 7, p 2107 (2024)
Object detection and tracking are pivotal tasks in machine learning, particularly within the domain of computer vision technologies. Despite significant advancements in object detection frameworks, challenges persist in real-world tracking scenarios,
Externí odkaz:
https://doaj.org/article/b376bd07860c4f46a453765356e30c60
Autor:
Richard Bustos, Stephen Andrew Gadsden, Mohammad Biglarbegian, Mohammad AlShabi, Shohel Mahmud
Publikováno v:
Energies, Vol 17, Iss 2, p 536 (2024)
Due to their nonlinear behavior and the harsh environments to which batteries are subjected, they require a robust battery monitoring system (BMS) that accurately estimates their state of charge (SOC) and state of health (SOH) to ensure each battery
Externí odkaz:
https://doaj.org/article/fdd3b54caf1f4e279ba5ed580839b960
Publikováno v:
Sensors, Vol 24, Iss 1, p 251 (2023)
This paper proposes a novel estimator for the purpose of fault detection and diagnosis. The interacting multiple model (IMM) strategy is effective for estimating the behaviour of systems with multiple operating modes. Each mode corresponds to a disti
Externí odkaz:
https://doaj.org/article/ef3c7f3bf96b4df1a5b638fc728210f1
Publikováno v:
Sensors, Vol 22, Iss 22, p 8927 (2022)
In this paper, a new filter referred to as the alpha sliding innovation filter (ASIF) is presented. The sliding innovation filter (SIF) is a newly developed estimation strategy that uses innovation or measurement error as a switching hyperplane. It i
Externí odkaz:
https://doaj.org/article/3bcef4c157e14e5285f23b0f2c885b16
Autor:
Saif Y. Alhammadi, Abdulla A. Alktebi, Abdelfattah E. Eldemiery, Victor Gillette, Mamdouh El Haj Assad, Mohammad AlShabi, Bassam A. Khuwaileh
Publikováno v:
Case Studies in Thermal Engineering, Vol 25, Iss , Pp 100894- (2021)
Advanced Power Reactor (APR-1400) is a Generation III + Pressurized Water Reactor (PWRs) and has gained popularity among energy mix community. APR-1400 features enhanced safety limits to prevent a “Fukushima-type” accident scenario for a duration
Externí odkaz:
https://doaj.org/article/99fcdb4f7f154ba084a01d862a25c0d3
Autor:
Ali A. Ismail, Nsilulu T. Mbungu, A. Elnady, Ramesh C. Bansal, Abdul-Kadir Hamid, Mohammad AlShabi
Publikováno v:
International Journal of Modelling and Simulation. :1-17
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a27cdb7d6f7ed9b352c54c8a7aa9620
https://doi.org/10.1080/02286203.2022.2148180
https://doi.org/10.1080/02286203.2022.2148180
Publikováno v:
International Journal of Robotics and Automation. 38
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::84352c2063364d31c058c1ad18e4337e
https://doi.org/10.2316/j.2023.206-0879
https://doi.org/10.2316/j.2023.206-0879