Department of Chemical and Metallurgical Engineering

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.
CMET_PCA group

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:

  1. Data
  2. Phenomenological and probabilistic modelling
  3. Statistical inference/learning
  4. 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.

Open positions
  • MSc Thesis:  Soft sensor for BOD and/or P for influent and/or primary treated wastewater based on data from a wastewater treatment plant (with Kemira, contact [email protected] and/or [email protected]
  • BSc Thesis: Literature review of soft sensors for BOD and P for influent and primary treated wastewater for wastewater treatment plants (with Kemira, contact [email protected] and/or [email protected])

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.

Iiro Harjunkoski

Latest publications:

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
More information on our research in the Research database.
Research database
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