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About

Najah Yousfi’s research lies at the intersection of advanced control theory and robotics, with a particular focus on fractional-order systems and intelligent navigation. Her major contributions center on developing robust control strategies for complex, multi-input multi-output (MIMO) systems, especially in motion control applications. She pioneered the integration of fractional calculus with the CRONE controller and quantitative feedback theory (QFT) to design prefilters and controllers that ensure stability and performance in uncertain environments. Her most cited work, “Path tracking design based on Davidson–Cole prefilter using a centralized CRONE controller applied to multivariable systems” (21 citations), demonstrates a novel approach to multivariable path tracking. She also made significant strides in mobile robotics, as seen in her 2010 paper “Optimized fuzzy controller for mobile robot navigation in a cluttered environment” (18 citations), where she used gradient-based optimization to tune a Sugeno fuzzy logic controller for obstacle avoidance and path planning. Her later work on fractional-order PD controllers for SCARA robots (2020) further extends robust motion control to industrial manipulators. With a citation count exceeding 50 across her key papers, Yousfi’s work is a valuable resource for researchers in fractional-order control, robust MIMO systems, and intelligent robotics.