Process control and automation
The group led by Prof. Francesco Corona and Prof. Iiro Harjunkoski is a trans-disciplinary research team that builds up on chemical engineering, applied mathematics and computer science. Our research is at the interface of automatic control, machine learning, and optimisation, we emphasise the computational and inferential thinking of process systems.
We develop fundamental methodologies and concrete tools of process control and process systems engineering that are capable of sensing, learning, reasoning, and actuating on chemical and physical systems based on observational data and domain knowledge.
The research develops on four foundational pillars:
- Phenomenological and probabilistic modelling
- Statistical inference/learning
- Optimal control/decision
The formal framework for modelling and control is given as a model of the system in which the uncertainties associated with our knowledge and the measuring process are clearly stated. An important objective in our research is the design and control of models that capture complex dynamics.
Research team members:
T106 Chemical and Metallurgical Eng
Filipe Pereira de Farias
Professorship strengthens the cooperation of ABB and Aalto in Industrial Internet solutions
Dr. Iiro Harjunkoski has been appointed Adjunt Professor at the School of Chemical Engineering.
Combining Machine Learning with Mixed Integer Linear Programming in Solving Complex Scheduling Problems
Iiro Harjunkoski, Teemu Ikonen 2022 14th International Symposium on Process Systems Engineering
Design of an Event-Driven Rescheduling Algorithm via Surrogate-based Optimization
Teemu Ikonen, Keijo Heljanko, Iiro Harjunkoski 2022 14th International Symposium on Process Systems Engineering
Likelihood Maximization of Lifetime Distributions With Bathtub-Shaped Failure Rate
Teemu J. Ikonen, Francesco Corona, Iiro Harjunkoski 2022 IEEE TRANSACTIONS ON RELIABILITY
Surrogate-based optimization of a periodic rescheduling algorithm
Teemu Ikonen, Keijo Heljanko, Iiro Harjunkoski 2022 AIChE Journal
Cross-domain fault diagnosis through optimal transport for a CSTR process
Eduardo Fernandes Montesuma, Michela Mulas, Francesco Corona, Fred Maurice Ngole Mboula 2022 IFAC-PapersOnLine
About the classical and structural controllability and observability of a common class of activated sludge plants
Otacilio B. L. Neto, Michela Mulas, Francesco Corona 2022 Journal of Process Control
Online optimal estimation and control for a common class of activated sludge plants
Otacílio B.L. Neto, Michela Mulas, Francesco Corona 2022 IFAC-PapersOnLine
Validation of an inverse model to determine ice load magnitude and load patch on a ship hull
Oskar Veltheim, Mikko Suominen, Teemu Ikonen, Pentti Kujala 2022 Proceedings of the 26th IAHR International Symposium on Ice
On the observability of activated sludge plants
Otacilio Bezerra Leite Neto, Michela Mulas, Francesco Corona 2021 IFAC-PapersOnLine
Predictive control of activated sludge plants to supply nitrogen for optimal crop growth
Otacilio Bezerra Leite Neto, Antoine Haddon, Farouk Aichouche, Jerome Harmand, Michela Mulas, Francesco Corona 2021 IFAC-PapersOnLine