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:
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
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
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