Process Control and Automation
The group, led by Prof. Sirkka-Liisa Jämsä-Jounela, aim to serve all fields of process technology - chemical, metallurgical and forest products - in terms of process automation.
The Research Group of Process Control and Automation is led by prof Sirkka-Liisa Jämsä-Jounela. The laboratory gives courses in process modelling, simulation, control, optimisation and automation as well as in production control. The undergraduate students typically have a few years background of process engineering studies, after which a one-to-two-year portion of automation studies. Post-graduate students typically work in the field of process technology - either in the industry or in research institutes or universities - while studying.
Latest publications
Department of Chemical and Metallurgical Engineering, Aalto University, Process Control and Automation
Optimal planning of municipal solid waste management systems in an integrated supply chain network
Publishing year: 2019
Computers and Chemical Engineering
Department of Chemical and Metallurgical Engineering, Process Control and Automation
Sustainable supply chain network design for the optimal utilization of municipal solid waste
Publishing year: 2019
AIChE Journal
Process Control and Automation, Department of Chemical and Metallurgical Engineering
Control strategy for a multiple hearth furnace in kaolin production
Publishing year: 2018
Control Engineering Practice
Process Control and Automation, Department of Chemical and Metallurgical Engineering
Simplified Mechanistic Model of the Multiple Hearth Furnace for Control Development
Publishing year: 2018
Simulation Notes Europe
Process Control and Automation, Department of Chemical and Metallurgical Engineering
Control Strategy For A Multiple Hearth Furnace
Publishing year: 2018
IFAC-PapersOnLine
Process Control and Automation, Department of Chemical and Metallurgical Engineering
Optimal control of a rougher flotation cell using adaptive dynamic programming
Publishing year: 2018
IFAC-PapersOnLine
Department of Chemical and Metallurgical Engineering, Process Control and Automation, Department of Media
A data-driven optimal control approach for solution purification process
Publishing year: 2018
Journal of Process Control
Department of Chemical and Metallurgical Engineering, Process Control and Automation
NEO-Fuzzy Neural Networks for Knowledge Based Modeling and Control of Complex Dynamical Systems
Publishing year: 2018
Department of Chemical and Metallurgical Engineering, Process Control and Automation
The impact of digitalization on the future of control and operations
Publishing year: 2018
Computers and Chemical Engineering
Research group members
