Data-driven adaptive integral variable structure control method for AGV trajectory tracking system based on BP neural network observer

Abstract To address the problem of insufficient control accuracy and robustness of automated guided vehicles (AGVs) under nonlinear time-varying conditions and external disturbances, a data-driven adaptive discrete-time integral sliding mode control (ADISMC) method is proposed. This method integrate...

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Detalhes bibliográficos

Principais autores:	Jianliang Xu, Jin Qian
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2026-06-01
coleção:	Scientific Reports
Assuntos:	Automated guided vehicle Trajectory tracking control Sliding mode control Neural network observer Dynamic linearization
Acesso em linha:	https://doi.org/10.1038/s41598-026-57374-9
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