Mohammad Mehdi Shahangian

Papers

Total Citations

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About

Mohammad Mehdi Shahangian is a researcher specializing in advanced control systems for robotic manipulators, with a focus on adaptive and robust control strategies. His major contributions lie in the development of hybrid control schemes that combine model reference adaptive control (MRAC) and sliding mode control (SMC) to enhance the precision and stability of robotic systems. In his most cited work, "An optimal MRAC–ASMC scheme for robot manipulators based on the artificial bee colony algorithm" (2021, 4 citations), Shahangian introduces an innovative approach that leverages the gradient descent method and the artificial bee colony optimization algorithm to design an optimal multi-adaptive robust controller. This work demonstrates his ability to integrate bio-inspired optimization techniques with classical control theory, addressing challenges in handling robot manipulators with uncertainties and nonlinear dynamics. While his citation count is still growing, his research represents a meaningful step toward more intelligent and adaptive robotic systems, offering practical solutions for real-world applications in automation and robotics. Shahangian’s work is particularly relevant for students and researchers interested in the intersection of adaptive control, optimization algorithms, and robotic manipulation.