An artificial systems, computational experiments and parallel execution‐based surface electromyogram‐driven anti‐disturbance zeroing neurodynamic strategy for upper limb human‐robot interaction control

In recent years, intelligent robots are extensively applied in the field of industry and rehabilitation, wherein human-robot interaction (HRI) control strategy is a momentous part that needs to be ameliorated. Specially, efficacy robustness HRI algorithm presence unknown external disturbances deserve addressed. To deal with these urgent issues, this study, artificial systems, computational experiments parallel execution framework constructed for control. The upper limb-robotic exoskeleton system re-modelled as an system. Depending on surface electromyogram-based subject's active motion intention practical system, non-convex function activated anti-disturbance zeroing neurodynamic (NC-ADZND) controller devised Furthermore, linear activation function-based (LAF-ZND) proportional-derivative (posterior deltoid (PD)) presented compared. Theoretical results substantiate global convergence proposed different disturbances. addition, simulation verify NC-ADZND better than LAF-ZND PD controllers respect order characteristics.