Luca Giulioni
Papers
2
Total Citations
39
H-Index
2
About
Luca Giulioni is a researcher in control systems engineering, with a primary focus on model predictive control (MPC) and its application to distributed and stochastic systems. His work addresses the challenge of coordinating multiple dynamically coupled subsystems, a key problem in modern automation and networked control. Giulioni’s most notable contribution is his development of a distributed predictive control algorithm for tracking problems, presented in his highly cited 2014 paper (34 citations). This method employs a hierarchical structure to ensure state and input constraints are satisfied while enabling effective coordination—a significant advance for complex, multi-agent systems. He has also explored stochastic model predictive control (SMPC), developing algorithms for discrete-time linear systems subject to additive disturbances and probabilistic constraints, as detailed in his 2015 thesis. With a combined citation count approaching 40, Giulioni’s research bridges theoretical rigor and practical application, offering tools for robust, real-time control in uncertain environments. His work is particularly relevant for students and researchers interested in distributed optimization, constraint handling, and the intersection of control theory with real-world industrial systems.
Research Focus
Key Achievements
Top Papers
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