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

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  • Razzaghian, Amir

Abstract

The paper investigates a novel fractional-order Lyapunov-based robust controller based on a fuzzy neural network (FNN) compensator for exoskeleton robotic systems. First, a finite-time fractional-order nonsingular fast terminal sliding mode control (FONFTSMC) method is designed. Second, a FNN algorithm is constructed to approximate the model uncertainty and external disturbances. Then, finite-time stability of the closed-loop control system is proved using Lyapunov stability theorem and adaptive law is derived through it. The proposed fuzzy neural network-based FONFTSMC (FNN-FONFTSMC) guarantees finite-time convergence and robustness against uncertainties for the exoskeleton robots trajectory tracking. Finally, to illustrate the effectiveness of the proposed control strategy, an upper-limb exoskeleton robot is provided as a case study in rehabilitation. The simulation results confirm the superiority of the proposed control method.

Suggested Citation

  • Razzaghian, Amir, 2022. "A fuzzy neural network-based fractional-order Lyapunov-based robust control strategy for exoskeleton robots: Application in upper-limb rehabilitation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 193(C), pages 567-583.
    • Handle: RePEc:eee:matcom:v:193:y:2022:i:c:p:567-583
    DOI: 10.1016/j.matcom.2021.10.022
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    References listed on IDEAS

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    1. Xiangjian Chen & Di Li & Pingxin Wang & Xibei Yang & Hongmei Li, 2020. "Model-Free Adaptive Sliding Mode Robust Control with Neural Network Estimator for the Multi-Degree-of-Freedom Robotic Exoskeleton," Complexity, Hindawi, vol. 2020, pages 1-10, March.
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    Cited by:

    1. Afkar, Mohammad & Gavagsaz-Ghoachani, Roghayeh & Phattanasak, Matheepot & Pierfederici, Serge, 2024. "Voltage-balancing of two controllers for a DC-DC converter-based DC microgrid with experimental verification," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 221(C), pages 159-179.
    2. Ayman A. Aly & Mai The Vu & Fayez F. M. El-Sousy & Ahmed Alotaibi & Ghassan Mousa & Dac-Nhuong Le & Saleh Mobayen, 2022. "Fuzzy-Based Fixed-Time Nonsingular Tracker of Exoskeleton Robots for Disabilities Using Sliding Mode State Observer," Mathematics, MDPI, vol. 10(17), pages 1-19, September.
    3. Ayman A. Aly & Kuo-Hsien Hsia & Fayez F. M. El-Sousy & Saleh Mobayen & Ahmed Alotaibi & Ghassan Mousa & Dac-Nhuong Le, 2022. "Adaptive Neural Backstepping Control Approach for Tracker Design of Wheelchair Upper-Limb Exoskeleton Robot System," Mathematics, MDPI, vol. 10(22), pages 1-16, November.

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    1. Ayman A. Aly & Kuo-Hsien Hsia & Fayez F. M. El-Sousy & Saleh Mobayen & Ahmed Alotaibi & Ghassan Mousa & Dac-Nhuong Le, 2022. "Adaptive Neural Backstepping Control Approach for Tracker Design of Wheelchair Upper-Limb Exoskeleton Robot System," Mathematics, MDPI, vol. 10(22), pages 1-16, November.

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