RBF neural network control for linear motor-direct drive actuator based on an extended state observer

DOI10.1155/2016/8390529zbMath1368.93662OpenAlexW2549623014WikidataQ59123673 ScholiaQ59123673MaRDI QIDQ2398539

Zhi Liu, Tefang Chen

Publication date: 16 August 2017

Published in: Discrete Dynamics in Nature and Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2016/8390529

zbMATH Keywords

extended state observerlinear motor-direct drive actuatorRBF neural network control

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Estimation and detection in stochastic control theory (93E10) Linear systems in control theory (93C05) Automated systems (robots, etc.) in control theory (93C85) Observability (93B07) Stochastic systems in control theory (general) (93E03)

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An energy-saving output feedback control of single-rod electrohydraulic servo system with disturbance observer

Cites Work

• Recursive terminal sliding mode control for hypersonic flight vehicle with sliding mode disturbance observer
• Extended state observer for uncertain lower triangular nonlinear systems
• Singularly perturbation method applied to multivariable PID controller design
• Active disturbance rejection control for nonlinear fractional-order systems
• Neural network-based adaptive consensus tracking control for multi-agent systems under actuator faults
• A New Extension of Newton Algorithm for Nonlinear System Modelling Using RBF Neural Networks

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