Mahdi Souzanchi-Kashani

Ferdowsi University of Mashhad, University of Shahrood

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About

Mahdi Souzanchi-Kashani’s research lies at the intersection of rehabilitation robotics, intelligent control systems, and human-robot interaction. His most cited work, “sEMG-based impedance control for lower-limb rehabilitation robot” (2017, 53 citations), demonstrates a pioneering approach to using surface electromyography signals to enable adaptive, patient-responsive robotic therapy—a key step toward more natural and effective rehabilitation. In another influential study, “Indirect adaptive fuzzy control for flexible-joint robot manipulators using voltage control strategy” (2015, 18 citations), he tackled the inherent complexity of flexible-joint manipulators by developing a novel control framework that accounts for nonlinearity, uncertainty, and actuator dynamics. This work advanced voltage-based control strategies for electrically driven robots, offering a more robust and computationally efficient alternative to traditional torque-based methods. Souzanchi-Kashani’s contributions are particularly notable for bridging theoretical control design with practical implementation in medical and industrial robotics. His research continues to influence the development of safer, more intelligent robotic systems that can adapt to human physiological signals and environmental uncertainties.