Manuel Gnucci
Papers
2
Total Citations
28
H-Index
2
About
Manuel Gnucci is a control systems researcher whose work focuses on the intersection of adaptive and learning control for complex mechanical systems, particularly underactuated and robotic platforms. His major contributions include the development of an adaptive tracking control strategy for underactuated mechanical systems with relative degree two, a challenging class of nonlinear systems where standard backstepping techniques fall short. This work, which has garnered 22 citations since 2021, addresses fundamental stability and tracking problems in systems like flexible-joint robots and overhead cranes. Gnucci has also advanced the field of repetitive learning control, demonstrating experimentally that a learning algorithm can achieve asymptotic joint position tracking for robotic manipulators with uncertain dynamics performing repetitive tasks. Notably, his work on periodic robot synchronization incorporates a recursive period identifier, enabling the controller to adapt to unknown or varying task periods in real time. These experimental validations bridge the gap between theoretical control design and practical implementation, marking Gnucci as a researcher dedicated to making sophisticated control theory work on real hardware.
Research Focus
Key Achievements
Top Papers
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