Stefano Longo

Papers

Total Citations

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About

Stefano Longo’s research lies at the intersection of adaptive control, networked systems, and friction compensation, with a focus on enhancing the performance and robustness of robotic and industrial automation. His most cited work, “Adaptive control of robotic servo system with friction compensation” (2011), introduces a continuously differentiable friction model integrated with neural network weight adaptation, enabling precise control of robotic turntable servo systems despite complex friction dynamics. This contribution addresses a critical challenge in motion control, offering a practical framework for improving accuracy in real-world robotic applications. Longo is also the author of the monograph “Optimal and Robust Scheduling for Networked Control Systems” (2013), which provides a rigorous theoretical foundation for scheduling controllers, sensors, and actuators in networked environments—a problem often solved heuristically in industry. While his citation counts reflect a focused, emerging impact, his work bridges theory and application, offering engineers and researchers actionable solutions for system integration. Longo’s contributions are particularly valuable for those working in robotics, automation, and control theory, where adaptive and networked control remain pivotal.