Stefano Bifaretti

University of Rome Tor Vergata, University of Nottingham

Papers

Total Citations

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About

Stefano Bifaretti is a leading researcher in advanced motion control systems, with a particular focus on permanent-magnet and hybrid step motors. His work addresses critical challenges in precision positioning, torque ripple mitigation, and adaptive control for repetitive tasks. Bifaretti’s most-cited paper, “Global Learning Position Controls for Permanent-Magnet Step Motors” (2011, 34 citations), introduces innovative learning-based control strategies that exploit the high efficiency, power density, and torque-to-inertia ratio of these motors, while overcoming nonuniform torque development. He further advanced the field with “Learning Position Controls for Hybrid Step Motors: From Current-Fed to Full-Order Models” (2018, 19 citations), which experimentally compares adaptive and repetitive learning controls for hybrid step motors in repetitive operations, offering a rigorous analysis of their benefits and limitations. This work bridges theoretical control models with practical implementation, providing engineers with robust solutions for high-precision automation. Bifaretti’s contributions are pivotal for applications in robotics, manufacturing, and servo systems, where accurate, repeatable motion is essential. His research continues to shape the design of intelligent, learning-based motor controllers, making him a key figure in modern motion control engineering.