Amir Razzaghian

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About

Amir Razzaghian is a leading researcher in the field of rehabilitation robotics, specializing in advanced control strategies for upper-limb exoskeletons. His work focuses on developing intelligent, robust control systems that enhance the safety and precision of robotic rehabilitation devices. Razzaghian’s most significant contribution is the introduction of a fuzzy neural network-based fractional-order Lyapunov robust control strategy, published in 2021, which has garnered 50 citations. This innovative approach integrates fuzzy logic and neural networks to handle system uncertainties and nonlinearities, significantly improving the performance of exoskeleton robots during rehabilitation therapy. His earlier foundational work on fuzzy sliding mode control for a 5-degree-of-freedom upper-limb exoskeleton (2015, 13 citations) demonstrated effective position tracking by combining inverse dynamics with sliding PID control to overcome unwanted uncertainties. Razzaghian’s research bridges theoretical control engineering with practical clinical applications, offering safer, more adaptive robotic assistance for stroke survivors and individuals with motor impairments. His work continues to influence the development of intelligent rehabilitation technologies, making robotic therapy more accessible and effective.