This article investigates the problem of dynamic memory event-triggered (DMET) fixed-time tracking control within time-varying asymmetric constraints for nonaffine nonstrict-feedback uncertain nonlinear systems with unmodeled dynamics and unknown disturbances. The existing dynamic event-triggered control methods cannot handle the nonlinear systems with unmodeled dynamics and nonaffine inputs, which greatly limits the applicability of the strategy. To this end, a novel DMET adaptive fuzzy fixed-time control protocol is constructed based on the idea of command filtered backstepping, in which a new dynamic signal function is established to deal with the unmodeled dynamics and an improved DMET mechanism (DMETM) is designed to solve the problem of nonaffine inputs. It is proved that the newly DMET control strategy ensures the tracking error converges to an arbitrarily small compact set in a fixed time and all the signals of the closed-loop systems are bounded. The effectiveness of the proposed approach is demonstrated by two simulation examples.
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http://dx.doi.org/10.1109/TCYB.2024.3386352 | DOI Listing |
J Adv Nurs
January 2025
School of Health, Policing and Sciences, University of Staffordshire, Staffordshire, UK.
Aim: To explore the perceptions and experiences of students raising concerns during pre-registration health and/or social care training in England.
Design: Systematic review.
Data Sources: MEDLINE, CINAHL, ERIC, PsycINFO and Education Research Complete were systematically searched for studies published between September 2015 and August 2024.
Nano Lett
January 2025
Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
Dielectric metasurfaces have emerged as an unprecedented platform for precise wavefront manipulation at subwavelength scales with nearly zero loss. When aiming at dynamic applications such as AR/VR and LiDAR, high-quality factor (high-Q) phase gradient metasurfaces have emerged as a way to boost weak light-material interactions in flat-optical components. However, resonant features are naturally tied to polarization, limiting devices to operating on a single polarization state, which reduces the efficiency and adaptability of wave-shaping.
View Article and Find Full Text PDFSci Rep
January 2025
College of Engineering, Applied Science University (ASU), Manama, Kingdom of Bahrain.
This paper presents an in-depth analytical investigation into the time-dependent flow of a Casson hybrid nanofluid over a radially stretching sheet. The study introduces the effects of magnetic fields and thermal radiation, along with velocity and thermal slip, to model real-world systems for enhancing heat transfer in critical industrial applications. The hybrid nanofluid consists of three nanoparticles-Copper and Graphene Oxide-suspended in Kerosene Oil, selected for their stable and superior thermal properties.
View Article and Find Full Text PDFSci Rep
January 2025
Instituto de Ingeniería Energética, Universitat Politècnica de València, Valencia, Spain.
Reliable prediction of photovoltaic power generation is key to the efficient management of energy systems in response to the inherent uncertainty of renewable energy sources. Despite advances in weather forecasting, photovoltaic power prediction accuracy remains a challenge. This study presents a novel approach that combines genetic algorithms and dynamic neural network structure refinement to optimize photovoltaic prediction.
View Article and Find Full Text PDFNat Commun
January 2025
Zhejiang Lab, Hangzhou, Zhejiang, 311121, China.
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