Joint dysfunction disables are impacting millions of individuals worldwide. It significantly interferes with essential daily tasks like eating, drinking, and writing, often making self-care challenging for those affected. Exoskeleton robots are developed to enable individuals with impaired physical functions to perform daily activities and maintain independence. This study introduces a wearable exoskeleton control system for the elbow joint designed, providing an alternative assistive solution to traditional treatment methods. The elbow exoskeleton system used for therapy has nonlinearity and time-dependent parameters. To address these challenges, this work presents a sliding mode control (SMC) for tracking the path of an EES. To reduce the chattering phenomenon in the SMC, power rate (PR) and boundary layer (BL) reaching laws are introduced. The heap-based algorithm (HBA) is used to tune design parameters of SMC. Massive simulations that were implemented in MATLAB confirmed the effectiveness of the suggested methodologies as they proved the reduction in the chattering and the improvement in the system performance. The simulation outcomes reveal that both approaches are able to eliminate the chattering phenomenon. However, the value of the IAE of the system controlled by SMC with the PR reaching law is reduced by 42.7% in compares with the system controlled by SMC with the BL reaching law. In addition, the IAE under uncertainty has been improved by 43.9%.
