Claudio Curcio

Papers

Total Citations

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About

Claudio Curcio’s research centers on advanced control theory and its application to precision motion systems, with a particular focus on trajectory tracking for uncertain dynamical systems. His major contribution lies in developing optimized control strategies for a recurring class of systems—including Cartesian robots, conveyor belts, and scanning devices used in medical imaging and near-field antenna characterization. In his most cited work (2018, 12 citations), Curcio addresses the challenging problem of raster scanning optimization in near-field measurements, proving key theorems for the design of PID controllers that ensure robust trajectory tracking despite system uncertainties. This work bridges theoretical control design with practical engineering needs, offering rigorous guarantees for real-world actuators. While his citation count reflects a focused, emerging impact, his contributions are notable for their direct applicability to high-precision instrumentation and measurement technologies. Curcio’s research is particularly valuable for engineers and researchers working on automated scanning systems, where accuracy and reliability are paramount. His work exemplifies how classical control theory can be adapted and optimized for modern, performance-critical applications.