Narges Gholami Mozafari
Papers
2
Total Citations
18
H-Index
2
About
Narges Gholami Mozafari is a researcher specializing in advanced control systems, particularly for continuum robot manipulators. Her work focuses on designing and tuning nonlinear controllers to address the inherent challenges of flexible, hyper-redundant robotic structures. Her major contributions include the development of a Lyapunov theory-based method for online tuning of premise and consequence fuzzy inference systems (FIS), integrated with sliding mode control to mitigate chattering while preserving robustness. She also pioneered a PID baseline fuzzy tuning approach for proportional-derivative coefficient nonlinear controllers, optimizing trajectory tracking in continuum robots. Her most cited papers, each garnering 9 citations, demonstrate foundational work in closed-loop control strategies that balance stability, precision, and adaptability. These contributions are particularly notable for addressing model uncertainties and external disturbances—critical issues in soft and continuum robotics. Mozafari’s research offers practical frameworks for enhancing the performance of flexible manipulators in applications ranging from medical surgery to industrial automation. Her work stands as a valuable resource for students and researchers exploring intelligent control, fuzzy logic, and nonlinear dynamics in robotic systems.
Research Focus
Key Achievements
Top Papers
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