A fuzzy neural network-based fractional-order Lyapunov-based robust control strategy for exoskeleton robots: application in upper-limb rehabilitation

DOI10.1016/J.MATCOM.2021.10.022OpenAlexW3211366736MaRDI QIDQ2060319

Amir Razzaghian

Publication date: 13 December 2021

Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.matcom.2021.10.022

zbMATH Keywords

fractional calculusfuzzy neural networkfinite-time stabilityLyapunov stability theoremterminal sliding mode controlexoskeleton robots

Mathematics Subject Classification ID

Biology and other natural sciences (92-XX) Systems theory; control (93-XX)

Related Items (1)

Model-free direct adaptive controller based on quantum-inspired fuzzy rules network for a class of unknown discrete-time systems

Cites Work

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• Mittag-Leffler stability of fractional order nonlinear dynamic systems
• Stability of fractional-order nonlinear dynamic systems: Lyapunov direct method and generalized Mittag-Leffler stability
• Fuzzy neural network and observer-based fault-tolerant adaptive nonlinear control of uncertain 5-DOF upper-limb exoskeleton robot for passive rehabilitation
• Fractional-order adaptive neuro-fuzzy sliding mode \(H_\infty\) control for fuzzy singularly perturbed systems
• Robust Adaptive Fractional‐Order Terminal Sliding Mode Control for Lower‐Limb Exoskeleton

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