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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Hlavní autoři:	Sergio Miguel Delfín-Prieto, Roberto Valentín Carrillo-Serrano, Ernesto Chavero-Navarrete, José Gabriel Ríos-Moreno, Mario Trejo-Perea
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2026-05-01
Edice:	Mathematics
Témata:	Fourier Series Neural Network discrete-time control Lyapunov stability magnetic levitation adaptive control Uniform Ultimate Boundedness
On-line přístup:	https://www.mdpi.com/2227-7390/14/10/1649
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