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About

Fatiha Loucif is a researcher at the forefront of intelligent control systems for robotics, specializing in the optimization of nonlinear controllers for robot manipulators. Her work bridges classical control theory and modern metaheuristic algorithms, with a particular focus on enhancing trajectory tracking performance. Her most influential contribution, the 2019 paper “Whale optimizer algorithm to tune PID controller for the trajectory tracking control of robot manipulator,” has garnered 196 citations, establishing her as a key figure in the application of bio-inspired optimization to robotic control. Loucif’s research systematically explores how evolutionary algorithms—including the Whale Optimizer, Antlion Optimization, Sine Cosine Algorithm, and Grey Wolf Optimizer—can be used to tune sliding mode controllers with PID surfaces, achieving robust and precise motion control. Her 2020 papers further extend this framework, demonstrating the synergy between sliding mode theory and nature-inspired optimization. By providing a systematic methodology for controller tuning, Loucif’s work offers practical solutions for industrial robotics, reducing manual calibration effort while improving system stability and accuracy. Her research is essential reading for students and engineers working on advanced robotic control and optimization.