Direct adaptive control for nonlinear systems using a TSK fuzzy echo state network based on fractional-order learning algorithm

DOI10.1016/J.JFRANKLIN.2021.09.015zbMath1478.93325OpenAlexW3203413003MaRDI QIDQ2058003

Lamiaa M. Elshenawy, Emad A. Elsheikh, Mohamed I. Abdo, Tarek A. Mahmoud

Publication date: 7 December 2021

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

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2021.09.015

zbMATH Keywords

adaptive controlnonlinear systemsfuzzy echo state neural networkractional-order sliding mode learning algorithm

Mathematics Subject Classification ID

Fuzzy control/observation systems (93C42) Nonlinear systems in control theory (93C10) Adaptive control/observation systems (93C40) Fractional derivatives and integrals (26A33) Variable structure systems (93B12) Networked control (93B70)

Related Items (2)

Model-free direct adaptive controller based on quantum-inspired fuzzy rules network for a class of unknown discrete-time systems ⋮ Passivity of fractional-order coupled neural networks with interval uncertainties

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