first_page Download PDF settings Order Article Reprints Open AccessArticle Muscle Fatigue Regulation through Muscle Activation Control in a Knee Hybrid Exoskeleton: Simulation Study by Shazan Ghajari 1, Reihaneh Kardehi Moghaddam 1,*, Hamidreza Kobravi 2 and Naser Pariz 3 [ORCID] 1 Electrical Engineering Department, Mashhad Branch, Islamic Azad University, Mashhad P.O. Box 9187147578, Iran 2 Research Center of Biomedical Engineering, Mashhad Branch, Islamic Azad University, Mashhad P.O. Box 9187147578, Iran 3 Department of Electrical Engineering, Faculty of Engineering, Ferdowsi University of Mashhad (FUM), Mashhad P.O. Box 9177948974, Iran * Author to whom correspondence should be addressed. Machines 2023, 11(10), 937; https://doi.org/10.3390/machines11100937 Submission received: 2 August 2023 / Revised: 31 August 2023 / Accepted: 5 September 2023 / Published: 1 October 2023 (This article belongs to the Section Automation and Control Systems) Download keyboard_arrow_down Browse Figures Review Reports Versions Notes Abstract The knee hybrid exoskeleton is a system that aids in the rehabilitation of patients with mobility disorders. It comprises a powered exoskeleton and functional electrical stimulation, which moves the knee joint by stimulating the muscles. However, electrical stimulation of muscles can lead to muscle fatigue. For the first time, this article investigates the regulation of muscle fatigue by controlling muscle activation. To control muscle activation, an innovative adaptive controller for FES is designed. The adaptation law is designed utilizing a time-varying estimation of the muscle activation time parameter. The proportional-integral controller is designed to regulate the knee joint angle utilizing an electrical motor. The proportional-integral controller gains are calculated using an optimization method. A cooperative control structure is presented to use the electrical motor and functional electrical stimulation simultaneously. The muscle activation error is uniformly ultimately bounded, and its boundedness is proven through Lyapunov analysis; the error bound is also determined. The simulation results showed knee joint angle regulation and muscle fatigue regulation. The proposed control method results were compared with those based on model predictive control and switching control, which showed significant improvement in the joint angle error and muscle fatigue. The proposed method is appropriate for practical implementation based on the obtained results.

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