Mahdi Baradarannia
Papers
6
Total Citations
77
H-Index
5
About
Dr. Mahdi Baradarannia is a leading researcher in advanced control systems, with a primary focus on the modeling and robust control of robotic manipulators and exoskeletons. His work is distinguished by a pioneering shift toward data-driven and model-free adaptive control methods, addressing the critical challenge of controlling complex, nonlinear robotic systems whose precise mathematical models are unknown. His major contributions include the development of novel iterative learning and terminal sliding mode control strategies that integrate data-driven linearization techniques, enabling high-precision trajectory tracking and robust performance under external disturbances and actuator nonlinearities like gear backlash. This is exemplified in his most-cited work, "Model-free adaptive iterative learning integral terminal sliding mode control of exoskeleton robots" (2021, 26 citations), which demonstrates a powerful approach for rehabilitation robotics. Further impact is seen in his adaptive robust control for manipulators with unknown backlash (2018, 21 citations) and his observer-based data-driven sliding mode control (2019, 15 citations). Dr. Baradarannia’s research also extends to multi-agent systems and inertial navigation, showcasing a broad expertise in creating intelligent, adaptive solutions for next-generation autonomous and robotic systems.
Research Focus
Key Achievements
Top Papers
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- 6Scaled consensus of descriptor multi-agent systems3 citations · 2017