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.
Published Version
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