Decentralized neural identification and control for uncertain nonlinear systems: application to planar robot

DOI10.1016/j.jfranklin.2009.10.019zbMath1201.93128OpenAlexW2053388904WikidataQ56424864 ScholiaQ56424864MaRDI QIDQ602670

Edgar N. Sanchez, Alexander G. Loukianov, Eduardo Jose Bayro Corrochano, Fernando Ornelas-Tellez

Publication date: 5 November 2010

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2009.10.019

zbMATH Keywords

identificationneural networkssliding modesdecentralized systemsEKF

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Neural networks for/in biological studies, artificial life and related topics (92B20) Nonlinear systems in control theory (93C10) Discrete-time control/observation systems (93C55) Automated systems (robots, etc.) in control theory (93C85) Identification in stochastic control theory (93E12)

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Uses Software

• Roboop

Cites Work

• A block method of synthesis of nonlinear systems at sliding modes
• Decentralized control design for large-scale systems with strong interconnections using neural networks
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