Babak Esmaeili
Papers
5
Total Citations
90
H-Index
5
About
Babak Esmaeili is a leading researcher in advanced robotics control, specializing in the development of intelligent, model-free control strategies for complex robotic systems. His work primarily focuses on exoskeleton robots, robotic manipulators, and pneumatic artificial muscles, addressing critical challenges in human-robot interaction and trajectory tracking. Esmaeili’s major contributions include pioneering the integration of adaptive backstepping, fast terminal sliding mode control, and iterative learning techniques to create robust controllers that operate without precise mathematical models. Notably, his 2019 paper on adaptive backstepping fast terminal sliding mode control for pneumatic artificial muscle actuators has garnered 33 citations, establishing a foundational approach for continuum modeling and dynamic formulation. His 2021 work on model-free adaptive iterative learning for exoskeletons, with 26 citations, offers a novel data-driven solution for reference tracking under external perturbations, significantly advancing wearable robot technology. Esmaeili’s research has also produced influential studies on data-driven observer-based control and fuzzy neural network sliding mode control, collectively demonstrating his impact with over 90 citations. His achievements include developing discrete-time predictive controllers that enable real-time adaptation, making him a key figure in the evolution of adaptive, model-free robotics for assistive and industrial applications.
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