Paolo Falcone

University of Sannio, Chalmers University of Technology

Papers

Total Citations

H-Index

About

Paolo Falcone’s research lies at the intersection of autonomous vehicle control, model predictive control (MPC), and networked control systems. His pioneering work on real-time MPC for autonomous active steering, published in 2006, directly tackled the computational bottleneck of nonlinear MPC, demonstrating that high-performance path stabilization could be achieved while satisfying real-time constraints—a foundational contribution to the field of autonomous driving. This paper, with 26 citations, remains a key reference for researchers developing safety-critical vehicle controllers. Falcone has also advanced the theory of networked control systems, introducing a novel reachability problem for systems where a master controller must schedule measurements from multiple slave nodes. His 2018 work on measurement scheduling for control invariance, with 11 citations, addresses fundamental challenges in robotics and intelligent transportation, where communication constraints can compromise stability. By bridging rigorous control-theoretic guarantees with practical implementation, Falcone’s work has shaped how engineers design reliable, real-time autonomous systems, making him a respected voice in both academic and applied control communities.