Mônica Félix receives the 2026 IFAC Triennial Journal Award for outstanding research in data-driven control
- Paris, France
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We are proud to celebrate an outstanding achievement from our tech team: Mônica S. Félix has received the 2026 IFAC Triennial Journal Award in the Survey category, recognizing the research paper she co-authored with Marcelo M. Morato, “Data Science and Model Predictive Control: A survey of recent advances on data-driven MPC algorithms.”
Published in the Journal of Process Control in December 2024, the paper provides a comprehensive review of recent developments in data-driven Model Predictive Control (MPC).
Bridging data science and advanced control
Model Predictive Control is a powerful approach for controlling systems to obtain optimal behavior. Traditionally, MPC relies on an accurate mathematical model of the process being controlled. However, building reliable models can become increasingly challenging when systems involve complex dynamics.
Data-driven approaches offer an alternative: instead of relying entirely on a predefined model, control strategies can make greater use of data collected directly from the system.
In their paper, Mônica Félix and Marcelo M. Morato review the growing body of research in this area and examine how data can be used to develop predictive control strategies. Their survey covers three main families of approaches: adaptive methods, machine-learning and reinforcement-learning-based approaches, and techniques based on behavioural theory and trajectory representations.
The authors also discuss the strengths and limitations of these different approaches, as well as the theoretical guarantees required for reliable implementation — including closed-loop stability, constraint satisfaction and recursive feasibility.
Recognizing research excellence
The IFAC Triennial Journal Awards recognize outstanding contributions published in IFAC journals and affiliated publications from the last three years. Receiving the 2026 award in the Survey category is a significant recognition of the relevance and quality of this research, and of the growing importance of data-driven control methods in modern engineering.
At Elum Energy, we are particularly proud to see this work recognized. Mônica’s research expertise in control and data-driven methods contributes to a culture of engineering excellence, innovation and continuous improvement — values that are central to the development of advanced energy management solutions.
Congratulations, Mônica, on this well-deserved achievement!
Read the award announcement:
Journal of Process Control – IFAC Triennial Journal Awards 2026
Read the research paper:
Data Science and Model Predictive Control – ScienceDirect
