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:
- Data
- 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.
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Research team members:
Related content:
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.
Latest publications:
Analytical methods for online data quality assessment
D. Aguado, J. Alferes, F. Arteaga, L. Belia, J. B. Copp, L. Corominas, F. Corona, A. Ferrer, H. Haimi, P. Kazemi, Q. H. Le, I. Miletic, M. Mulas, A. Robles, M. V. Ruano, S. Russo, O. Samuelsson, J. P. Steyer, K. Villez, E. I.P. Volcke, M. J. Wade, J. Zambrano
2024
Metadata Collection and Organization in Wastewater Treatment and Wastewater Resource Recovery Systems
A model-based framework for controlling activated sludge plants
Otacílio B.L. Neto, Michela Mulas, Francesco Corona
2024
Chemical Engineering Journal
Block particle filters for state estimation of stochastic reaction-diffusion systems
José Augusto F. Magalhães, Otacilio B. L. Neto, Francesco Corona
2023
IFAC-PapersOnLine
A Bayesian inferential sensor for predicting the reactant concentration in an exothermic chemical process
Teemu Ikonen, Samuli Bergman, Francesco Corona
2023
Chemometrics and Intelligent Laboratory Systems
End-effect mitigation in multi-period stochastic programming of energy storage operations
Teemu Ikonen, Dongho Han, Jay H. Lee, Iiro Harjunkoski
2023
33rd European Symposium on Computer Aided Process Engineering
Likelihood Maximization of Lifetime Distributions With Bathtub-Shaped Failure Rate
Teemu J. Ikonen, Francesco Corona, Iiro Harjunkoski
2023
IEEE Transactions on Reliability
Stochastic programming of energy system operations considering terminal energy storage levels
Teemu J. Ikonen, Dongho Han, Jay H. Lee, Iiro Harjunkoski
2023
Computers and Chemical Engineering
Evidence of waste management impacting severe diarrhea prevalence more than WASH : An exhaustive analysis with Brazilian municipal-level data
Anni Juvakoski, Henrik Rantanen, Michela Mulas, Francesco Corona, Riku Vahala, Olli Varis, Ilkka Mellin
2023
Water Research
Roadmap towards smart wastewater treatment facilities
Daniel Aguado García, Henri Haimi, Michela Mulas, Francesco Corona
2022
2nd International Joint Conference on Water Distribution Systems Analysis & Computing and Control in the Water Industry
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
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