Alessandro Tenaglia

Alessandro Tenaglia

Ph.D. Student in Automation and Control Engineering

University of Rome Tor Vergata

Biography

Alessandro Tenaglia was born in Rome, Italy, in 1997. He received a Bachelor’s Degree in Computer Engineering and a Master’s Degree in Automation Engineering from the University of Rome Tor Vergata, both summa cum laude, in 2019 and 2021, respectively. He is currently pursuing a Ph.D. program in Computer Science, Control, and Geoinformation at the University of Rome Tor Vergata. His research interests include control allocation techniques, magnetic control of tokamak plasmas, and autonomous navigation algorithms for unmanned systems. Since 2021, he has actively contributed to the University of Rome Tor Vergata team, participating in the Leonardo Drone Contest, leading to the victory of various awards. Currently, he is pursuing a one-year visiting period at the Swiss Plasma Center, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, working on the magnetic control system of the TCV tokamak.

Interests
  • Artificial Intelligence
  • Control allocation
  • Control of tokamak plasmas
  • Unmanned systems
Education
  • Visiting Ph.D. Student at Swiss Plasma Center, today

    Ecole Polytechnique Fédérale de Lausanne (EPFL)

  • Ph.D. Student in Computer Science, Control, and Geoinformation, today

    University of Rome Tor Vergata

  • MSc in Automation Engineering, 2021

    University of Rome Tor Vergata

  • BSc in Computer Science, 2019

    University of Rome Tor Vergata

Experience

 
 
 
 
 
University of Rome Tor Vergata
Ph.D. Student
November 2021 – Present Italy
PhD program in Computer Science, Control and GeoInformation
 
 
 
 
 
Ecole Polytechnique Fédérale de Lausanne (EPFL)
Visiting Ph.D. Student at Swiss Plasma Center
May 2023 – April 2024 Switzerland
Topic: Magnetic control system of the TCV tokamak

Projects

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Leonardo Drone Contest
An open innovation challenge by Leonardo
Leonardo Drone Contest

Publications

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(2023). A Trajectory Based Optimization Approach for Hybrid Observer Design. 2023 62nd IEEE Conference on Decision and Control (CDC).

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(2023). A Trajectory-Based Stochastic Approach to Symbolic Control. 2023 62nd IEEE Conference on Decision and Control (CDC).

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(2023). Efficient Visual Sensor Fusion for Autonomous Agents. 2023 International Conference on Control, Automation and Diagnosis (ICCAD).

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(2023). A Novel Distributed Architecture for Unmanned Aircraft Systems Based on Robot Operating System 2. IET Cyber-Systems and Robotics.

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(2023). A Robust Optimization Approach for Dynamic Input Allocation. IFAC-PapersOnLine.

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Talks

IEEE CDC 2023
Paper presentation
IEEE CDC 2023
IFAC World Congress 2023
Paper presentation
IFAC World Congress 2023
Droni a volo autonomo
Seminar
Droni a volo autonomo

Gallery

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