Intelligent Machines and Systems suomeksi 
WELCOME
TO THE WWW-PAGES OF THE SYSTEMS ENGINEERING RESEARCH GROUP!
Systems
Engineering, together with the group of Mechatronics and machine diagnostics,
forms the research unit of Intelligent Machines and Systems (IMS). IMS is the
automation unit of the Faculty of Technology at the University of Oulu.
The Systems
Engineering research group focuses on theory, methods and applications of
process control and systems engineering, energy systems in particular. Our
field of research includes the following fields:
·
modeling
of system dynamics,
· estimation and identification,
· control,
· optimization and decision making.
Systems Engineering staff:
·
Enso
IKONEN, full professor of control and systems
engineering, PhD
·
Jukka
HILTUNEN, lecturer, degree program leader, PhD
(licentiate)
·
István
SELEK, post.doc researcher, adjunct professor of
dynamic process and energy systems, PhD
·
Jenö
KOVÁCS, university researcher, adjuct professor
of power plant automation, PhD
·
Joni
VASARA, M. Sc, doctoral student
·
Pierre
JAOUEN, M.Sc, doctoral student
·
Tommi
KONTTINEN, research assistant, diploma worker
·
Manne
TERVASKANTO, PhD (licentiate), part-time teacher
Contact info: FirstName.LastName@oulu.fi or consult the phone book of
the University of Oulu.
Latest
news from Systems Engineering:
·
AI
automation solution for PVO Vesivoima (link)
9/2024
·
Video
demonstrations from the COGNITWIN-project on tools and fouling management
2/2023:
Recent
publications:
o
Vasara, J., I. Selek. and E. Ikonen (2025)
Hybrid power plant in FCR-N provision: An analysis of storage sizing in
connection with turbine stress reduction. Electric Power Systems Research,
239, Feb 2025 https://authors.elsevier.com/sd/article/S0378-7796(24)01129-5
o Vasara,
J., I. Selek. and E. Ikonen (2024) Sizing of energy storage for hybrid
power plants aiming for turbine stress reduction under FCR-N requirements.
Journal of Energy Storage 103, Part A, 1 December 2024 https://www.sciencedirect.com/science/article/pii/S2352152X24038064
o Ikonen,
E., M. Liukkonen, A. Hansen, M. Edelborg, O. Kjos, I. Selek and A. Kettunen
(2023) Fouling monitoring in a circulating fluidized bed boiler using direct
and indirect model-based analytics. Fuel, 346, pp. 128341. https://doi.org/10.1016/j.fuel.2023.128341
o Johansen,
S. T., P. Unal, Ö. Albayrak, E. Ikonen,
K. J. Linnestad, S. Jawahery, A. K. Srivastava, B. T. Løvfall (2023)
Hybrid and Cognitive Digital Twins for the Process Industry. Open
Engineering, 23, pp. 1–13 https://doi.org/10.1515/eng-2022-0418
o
Ikonen, E., T. Liedes and J. Vasara
(2023) Model predictive controlled subsurfacedrainage and irrigation for
peatland groundwater management. 22nd IFAC World Congress,
9-14 June 2023, Yokohama https://www.sciencedirect.com/science/article/pii/S2405896323010418.
o Ikonen,
E., J. Torvela, M. Törmälä, J. Savela, M. Pylvänäinen, J. Vasara and T. Liedes
(2023) Subsurface drainage and irrigation automation for cultivated land
groundwater management. Automaatiopäivät / Automation Days (AP/AD 2023),
28-29 March 2023, Helsinki. (Long abstract, presentation slides)
·
Selected papers before 2023:
o Vasara, J., I. Selek and E. Ikonen (2022) Stress
reduction of turbine units in hybrid power plants: an operational perspective. 10th
International Conference on Control, Mechatronics and Automation (ICCMA
2022), Luxembourg 9–12 Nov 2022.
o
Neuvonen, M., I. Selek, E. Ikonen and L.
Aho (2022) Heat exchanger fouling estimation for
combustion–thermal power plants including load level dynamics. International
Conference on Systems, Man and Cybernetics (IEEE SMC 2022) 9–12 Nov 2022, Prague (IEEE Xplore)
o
Ikonen, E. M. Neuvonen, I. Selek, M.
Salo, M. Liukkonen (2022) On-line estimation of circulating
fluidized bed boiler fuel composition. 2022 UKACC 13th International
Conference on Control (CONTROL 2022), 20-22 April 2022, Plymouth, UK. (IEEE Xplore)
o
Ikonen, E. and I. Selek
(2021) Fusing Physical Process Models with Measurement Data Using FIR
Calibration, Control Engineering and Applied Informatics, 23, nro
2, pp. 67-76. (CEAI)
o
Zotică, C., L.
Nord, J. Kovács, S. Skogestad (2020) Optimal operation and control of heat to
power cycles: a new perspective from a systematic plantwide control approach. Computers
and Chemical Engineering, 141. (CCE)
Systems
Engineering is strong in methods: including physical and experimental
modeling of dynamic systems, theory of estimation and control, and methods of
optimization, artificial intelligence, and operations research.
Selected publications:
Selek, I., J. Vasara and E. Ikonen (2022) Generalized orthogonalization: a unified framework for Gram-Schmidt orthogonalization, SVD and PCA. International Conference on Systems, Man and Cybernetics (IEEE SMC 2022) 9–12 Nov 2022, Prague (IEEE Xplore)
Ikonen, E. and I. Selek (2021) Fusing Physical Process Models with Measurement Data Using FIR Calibration, Control Engineering and Applied Informatics, 23, nro 2, pp. 67-76. (CEAI)
Selek, I. and E. Ikonen (2019) Role of specific energy in the decomposition of time-invariant least-cost reservoir filling problem. European Journal of Operational Research, 272 (2), pp. 565-573
Selek, I and E. Ikonen (2019) Fundamental Limitations
of the Decay of Generalized Energy in Controlled (Discrete–Time) Nonlinear
Systems Subject to State and Input Constraints. Int. J Applied Mathematics
and Computer Science, 29 issue 4. (AMCS)
Ikonen, E., I. Selek and K. Najim (2016) Process control using finite Markov chains with iterative clustering. Computers & Chemical Engineering, 93, 293–308.
Najim, K., E. Ikonen and P. Del Moral (2006). Open-loop regulation and tracking control based on a genealogical decision tree. Neural Computing & Applications, 15, no. 3/4, pp. 339-349.
Najim, K., A. Poznyak and E. Ikonen (2004). Optimization based on a team of automata with binary outputs. Automatica, 40(8), pp. 1349-1359.
We apply
our methods and process knowedge in central application area of automation engineering:
· monitoring,
·
process
control, short term optimisation,
· maintenance.
We
emphasize on scientific skills needed in control of dynamic energy systems. We
cooperate with the worlds largest CFB boiler manufacturer (Sumitomo SHI FW
Energia Oy). We work actively together with the energy and process industry. You can find our project portfolio here.
Our
education covers
control theory from basics to advanced methods, automation infrastructure, and
applications of automation in the process industry. We supervise theses at all
levels: B.Sc, M.Sc and Ph.D. We organize post graduate courses for the needs of
our doctoral students. We develop education in automation in close cooperation
with the educators at the Oulu region.
Selected publications:
Hiltunen,
J., E-P Heikkinen, J Jaako, J Ahola (2011). Pedagogical
basis of DAS formalism in engineering education. European Journal of Engineering Education, 36 (1) pp. 75-85.
Honkanen, S. (2011) Tekniikan ylioppilaiden valmistumiseen johtavien opintopolkujen mallintaminen - perusteena lukiossa ja opiskelun alkuvaiheessa saavutettu opintomenestys. Acta Universitatis Ouluensis C376.
Najim, K., E. Ikonen and D. Aït-Kadi (2004). Stochastic Processes: Estimation, Optimization and Analysis. Kogan Page Science, London, U.K. (text book) ISBN 1903996554.
Ikonen, E. and K. Najim (2002). Advanced Process Identification and Control, Marcel Dekker Inc., New York, U.S.A., 310 p. (text book) ISBN 0-8247-0648-X.
Najim, K. and E. Ikonen (1999) Outils mathématiques pour le génie des procédés. Dunod Editeur, Paris, France, 223 p. (text book) ISBN 2 10 004591 1
Systems
Engineering project portfolio
A central theme of our project portfolio is in industrial applications of energy engineering. Here are some samples:
· In circulating fluidized bed (CFB) modeling and control, we cooperate with Sumitomo SHI FW Energia Oy. SFW is the worlds largest CFB boiler manufacturer.
o
OffgridH2
(2024) on SOEC conceptual control design, with links to CLIC OffgridH2.
o
CaLby2030
(2024) on CaL process conceptual control design, linking to the EU-Horizon CaLby2030 project.
o
SmartFlex
(2020–2023) considers agile CFB automation.
o
In
a long series of CFBCON projets (2010–2020 ) topics in CFB modeling and control
have been considered.
o
In
COMBO-CFB (2014-16) joint CFB + CSP production was examined (concentrated solar
power), in cooperation with VTT.
Selected publications:
Ikonen, E.,
M. Liukkonen, A. Hansen, M. Edelborg, O. Kjos, I. Selek and A. Kettunen (2023)
Fouling monitoring in a circulating fluidized bed boiler using direct and
indirect model-based analytics. Fuel, 346, pp. 128341. https://doi.org/10.1016/j.fuel.2023.128341
Neuvonen, M., I. Selek, E. Ikonen and L. Aho (2022) Heat exchanger fouling estimation for combustion–thermal power plants including load level dynamics. International Conference on Systems, Man and Cybernetics (IEEE SMC 2022) 9–12 Nov 2022, Prague (IEEE Xplore)
Zotică,C., L. Nord, J. Kovács, S.Skogestad (2020) Optimal operation and control of heat to power cycles : a new perspective from a systematic plantwide control approach. Computers and chemical engineering, 141,
Hultgren, M., E. Ikonen and J. Kovacs (2019). Integrated Control and Process Design for Improved Load Changes in Fluidized Bed Boiler Steam Path. Chemical Engineering Science, 199, pp. 164-178.
Niva, L. (2018) Self-optimizing control of
oxy-combustion in circulating fluidized bed boilers. Acta Universitatis Ouluensis. C, Technica. http://jultika.oulu.fi/Record/isbn978-952-62-2130-4
Hultgren, M., E., Ikonen and J. Kovacs (2017) OTU-CFB boiler control design with the dynamic relative gain array and partial relative gain. Industrial & Engineering Chemistry Research, 56 (48), pp. 14290-14303
Selek I., Kovacs J., Ikonen E. and A. Kettunen (2017) COMBO-CFB: Integration of concentrated solar power with circulating fluidized bed power plants. 12th International Conference on Fluidized Bed Technology (CFB-12) 23-26 May, Krakow, Poland.
Niva, L., E. Ikonen and J. Kovács (2015). Self-optimizing control structure design in oxy-fuel circulating fluidized bed combustion, International Journal of Greenhouse Gas Control, 43, 93-107.
Hultgren, M., E. Ikonen, J. Kovács, (2014) Oxidant Control and Air-Oxy Switching Concepts for CFB Furnace Operation. Computers & Chemical Engineering, 16, pp 203-219.
Ikonen, E., J. Kovacs and J. Ritvanen (2013) Circulating fluidized bed hot loop analysis, tuning and state-estimation. International Journal of Innovative Computing, Information and Control, 9 (8) , pp. 3357-3376.
Ikonen, E., K. Najim and U. Kortela (2000). Neuro-fuzzy modelling of power plant flue-gas emissions. Engineering Applications of Artificial Intelligence, 13, no. 6, pp. 705–717.
Matias
Hultgren PhD defence on Control design for CFB boilers integrated with process
design, 3 Dec 2021: dissertation.
·
Hydropower dynaamic
modeling, control and optimization
o
A
series of projects with PVO Vesivoima Oy (2017-2025) has considered
participation to the frequency control markets as well as integration of
batteries to production. The
developed control is applied, patenting is under work.
o
In
a project on daily optimization (2020) a
model for the Ii-river basins was constructed, and an optimization problem was
formulated and solved.
Vasara, J.,
I. Selek. and E. Ikonen (2025) Hybrid power plant in FCR-N provision: An
analysis of storage sizing in connection with turbine stress reduction.
Electric Power Systems Research, 239, Feb 2025 link
Vasara, J.,
I. Selek. and E. Ikonen (2024) Sizing of energy storage for hybrid power plants
aiming for turbine stress reduction under FCR-N requirements. Journal of Energy
Storage, 103, Part A, 1 December 2024 link
Vasara, J.,
I. Selek and E. Ikonen (2022) Stress reduction of turbine units in hybrid power
plants: an operational perspective. 10th International Conference on Control,
Mechatronics and Automation (ICCMA 2022), Luxembourg 9–12 Nov 2022.
Vasara, J., I. Selek and E. Ikonen (2021) Asymptotic analysis of a control–oriented open channel flow model. Int. Conf. on Systems and Control (ICSC’21), 24-26 Nov 2021, Caen, France, 2021. (IEEE Xplore)
Pohjolan Voima (2020) Cooperation within networks. (link)
·
Automation
in agriculture and land use
o
We
participate to actions of the Digital
Waters -flagship of the Academy of Finland (2024-2027).
o
TurPo (2022-2025) considers
peatland water management using catchment scale evaluation and ground water
table height monitoring. In cooperation with Luke, Uponor and Valio.
o
Vesihiisi
(2021-2023) examined water control in peat lands using control wells, in
cooperation with Luke (Natural Resources Institute Finland), MML
(National Land Survey of Finland) and salaojayhdistys (Finnish Field
Drainage Association).
o
ESKE
(2021-2022) built the infrastruture of a single controlled subsurface drainage
well.
o
PeltoSäätö
pilots controlled subsurface drainage in cooperation with kpedu.
Ikonen, E., T. Liedes and J. Vasara (2023) Model predictive controlled subsurfacedrainage and irrigation for peatland groundwater management. 22nd IFAC World Congress, 9-14 June 2023, Yokohama
·
Digital twins, artificial ingelligence and machine learning (AI/ML, IoT)
o
COGNITWIN
was a Horizon 2020 SPIRE project (2019–2023), participated by e.g. SINTEF,
Cybernetica, Fraunhofer and SFW. The projects looked at digital
twins and their development towards cognitive properties. We apply results for
fuel feed and surface fouling on-line analytics. See www.cognitwin.eu or the UOULU COGNITWIN www-page.
o During professor’s pool research leave (2015–16) Markov chains in process control were examined , in a visit at UMA/ISA Málagassa. Application area included also mechatronics.
Selected publications:
Johansen, S. T., P. Unal, Ö. Albayrak, E. Ikonen, K. J. Linnestad, S. Jawahery, A. K. Srivastava, B. T. Løvfall (2023) Hybrid and Cognitive Digital Twins for the Process Industry. Open Engineering, 23, pp. 1–13 https://doi.org/10.1515/eng-2022-0418
Ikonen, E. and I. Selek (2021) Fusing Physical Process Models with Measurement Data Using FIR Calibration, Control Engineering and Applied Informatics, 23, nro 2, pp. 67-76. (CEAI)
E. Ikonen and I. Selek (2020) Calibration of Physical Models with Process Data using FIR Filtering, 2020 Australian and New Zealand Control Conference (ANZCC), Gold Coast, Australia, 2020, pp. 143-148.
Rankinen, A., E. Ikonen and T. Liedes (2018) Validation of a nonlinear two-dimensional MacPherson suspension system model with multibody simulations. International Conference on Mechatronic and Embedded Systems and Applications (IEEE ASME MESA 2018), 2-4 July, Oulu, Finland
Ikonen, E. (2017) Active suspension control with state estimation using finite Markov chains. International Journal of Advanced Mechatronic Systems 7 (3) 183–192.
Ikonen, E., I. Selek and K. Najim (2016) Process control using finite Markov chains with iterative clustering. Computers & Chemical Engineering, 93, 293–308.
·
Water and district heating network operation optimization
o
In
EaaSlab (2019–2021) an energy pilot environment was developed. The role of
IMSin was to build a digital twin for the district heating network. The project
is in cooperation with Oulu University of Applied Sciences.
o
In
an Academu of Finland project OPUS (2011–2014) the application was the modling
and pump scheduling of the water network at the city of Sopron. Project was
conducted in cooperation with BUTE/HDS from Budapest.
o
In
the DINO subproject (OPUS, 2013–2014) the target was the Kemi district heating
network modeling and dynamic optimization of operation, in cooperation with Kemin
Energia.
o
Simulation of district heating network of city
of Kemi, impact of external heat source (5 min steps).
Selected publications:
Selek, I. and E. Ikonen (2019) Role of specific energy in the decomposition of time-invariant least-cost reservoir filling problem. European Journal of Operational Research, 272 (2), pp. 565-573
Ikonen, E., I. Selek, J. Kovacs & M. Neuvonen (2016). Examination of operational optimization at Kemi district heating network. Thermal Science 20 (2), pp 667-678 (link to TS)
Bene, J. (2013) Pump schedule optimisation
techniques for water distribution systems. Acta Universitatis Ouluensis. C, Technica. http://jultika.oulu.fi/Record/isbn978-952-62-0266-2
Selek, I., J. Bene and E. Ikonen (2013) Utilizing permutational symmetries by dynamic programming – Application for the optimal control of water distribution systems under water demand uncertainties. International Journal of Innovative Computing, Information and Control, 9 (8), pp. 3091-3114.
Ikonen, E, I. Selek and J. Bene (2012). Optimization of pumping schedules using the genealogical decision tree approach. Chemical Product and Process Modeling, 7 (1), 1-25.
·
Optimization
of demand response in buildings
o
IN
VIRPA-project (2015–2017) the freezers/refrigrators of a supermarket were
modelled, and dynamic optimization of storage capacity was designed. The
project partners included VTT, Jetitec, S-Voima, Rejlers and Fingrid.
Selected publications:
Ikonen, E. and I. Selek (2018) Dynamic modelling and optimization of a supermarket CO_2 refrigeration system for demand side management. 15th International Conference on Electrical Engineering, Computing Science and Automatic Control (IEEE CCE 2018), 5-7 Sept 2018, Mexico City.
·
Education in automation/pilot-environments
o
OTTO
(2024-2025) projet supports algorithmic thinking.
o
KOTODIPPI
(2021-2023) looked at improving digital education readiness, via Stack and
GeoGebra -trainings in particular.
o
ELVIS
(2021-2023) concerns continuous learning, taking advantage of the hybrid
laboratory environment. In cooperation with Oulu UAS and school of
vocational teacher education. Our role is in exploiting digital twins in a
simulation laboratory.
o
Automation
environments are a part of the hybrid laboratory EaaSlab (2019–2021), including
heat production, heat network, heat exchangers, electrical network, solar
panels, HVAC, automation and maintenance education pilot environments at the
university campus.
o
Automation
education pilot environments and working-life oriented education were the
themes of EduAuto/DigiAuto (2017–2019), in cooperation with Oulu University
of Applied Sciences and the regional educational consortium OSAO.
last
updated 26 Nov 2024 / Enso
Avainsanoja
Prosessien
säätö säätötekniikka ohjaus prosessinohjaus process control automaatio
automation process automation prosessiautomaatio ennustava säätö
malliprediktiivinen säätö MPC model predictive control kehittynyt säätö
advanced control
tilaestimointi
state estimation monitorointi process monitoring prosessin seuranta Kalman
filtteri Kalman suodin Kalman filter UKF unscented Kalman filtering EKF
partikkelifiltteri particle filtering bayesian state estimation bayesilainen
tilaestimointi
tekoäly ML AI
koneoppiminen artificial inteligence IoT koneiden internet laitteiden internet
neuroverkko sumea neural network fuzzy Markov chains Markovin ketjut finite
state learning automata dynaaminen ohjelmointi Markovin prosessit dynamic
programming Markov decision processes MDP
Matlab mallintaminen prosessien mallinnus dynaminen
mallintaminen identifiointi estimointi data-driven modeling mittausperustainen
mallintaminen datapohjainen mallintaminen Simulink SimScape Control System
Toolbox
leijukerroskattila kiertopeti kiertoleijupeti CFB
circulating fluidized bed boiler power plants voimalaitos voimalaitosautomaatio
voimalaitosten säätö BFB CFBB AFB kupliva peti energiantuotanto puu hiili hake
wood chips peat turve jätepuu RDF demolition wood flue gas emissions
savukaasupäästöt kaukolämpö kulutusjousto district heating demand response