Papers
2
Total Citations
30
H-Index
2
About
Jalil Sadati is a researcher whose work sits at the intersection of advanced control theory and robotics, with a particular focus on fractional-order iterative learning control (ILC). His key research areas include nonlinear system control, sliding mode control, and intelligent optimization methods for robotic manipulators. Sadati’s major contributions lie in pioneering the integration of sliding mode controllers with fractional-order ILC, as demonstrated in his most-cited paper (2016, 27 citations), which was the first to combine these approaches for nonlinear systems under bounded disturbances. This work offers a robust solution for improving tracking performance in uncertain environments. Additionally, his 2017 paper (3 citations) explores intelligent fractional-order ILC using feedback linearization and biogeography-based optimization (BBO) for single-link robots, advancing adaptive control strategies. While his citation counts reflect a growing but specialized impact, Sadati’s innovations are notable for pushing the boundaries of iterative learning in robotics, offering new pathways for precision control in complex, real-world applications. His work is particularly valuable for students and researchers interested in fractional calculus, robust control, and intelligent systems.
Research Focus
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Top Papers
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