Selma Sefriti

Papers

Total Citations

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About

Selma Sefriti is a researcher specializing in advanced control systems, robotics, and intelligent control methodologies, with a particular focus on addressing the challenges of nonlinear and uncertain dynamical systems. Her most impactful work centers on the development of hybrid control strategies that synergize classical techniques with computational intelligence, most notably the integration of sliding mode control (SMC) with fuzzy logic and neural networks for robotic applications. Sefriti's most cited contributions, each garnering 22 citations, demonstrate her innovative approach to solving the well-known chattering problem inherent in standard sliding mode controllers. Her 2012 papers introduced both fuzzy-sliding mode and adaptive neural network-sliding mode frameworks applied to two-link robot manipulators, achieving robust tracking control while significantly reducing performance limitations associated with conventional methods. Her 2014 work further refined fuzzy sliding mode control for complex nonlinear robotic systems, accumulating 17 citations and reinforcing her standing in the field. With a combined citation impact of over 60 across her top works, Sefriti has made meaningful contributions to the robotics and control engineering community. Her research is particularly valuable for students and practitioners seeking practical, intelligent solutions to real-world challenges in robot manipulator control and automation systems.