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Discrete-Time Fourier Series Neural Network Control for Nonlinear SISO Systems: Validated in a Magnetic Levitation Model

The control of nonlinear, open-loop unstable dynamics is a prevalent engineering challenge, often benchmarked through magnetic levitation (Maglev) systems. While continuous-time adaptive neural networks are commonly used to reject disturbances, their direct digital implementation often induces close...

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Principais autores: Sergio Miguel Delfín-Prieto, Roberto Valentín Carrillo-Serrano, Ernesto Chavero-Navarrete, José Gabriel Ríos-Moreno, Mario Trejo-Perea
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2026-05-01
Serier:Mathematics
Fag:
Fourier Series Neural Network
discrete-time control
Lyapunov stability
magnetic levitation
adaptive control
Uniform Ultimate Boundedness
Online adgang:https://www.mdpi.com/2227-7390/14/10/1649
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