Intelligent Machines and Systems           suomi

 

 

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

·        Markus NEUVONEN, M.Sc., doctoral student

·        Lauri AHO, graduate 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:

          

 

      
COGNITWIN (EU H2020 Spire) videodemonstrations (Feb 2021 and Feb 2022).

 

PhD defence of Matias Hultgren on Control Design for CFB Boilers Integrated with Process Design, 3 Dec 2021 at 13, L6, Linnanmaa, Oulu (thesis)

Recent publications:

·        Ikonen, E., M. Neuvonen, I. Selek, M. Salo and M. Liukkonen. On-line estimation of circulating fluidized bed boiler fuel composition (2022). 13th UK Automatic Control Council (UKACC) International Conference (CONTROL2022) Oct 2021, 22–24 April 2022, Plymouth, UK (to appear)

·        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)

·        Liukkonen, M., A. Kettunen, J. Miettinen, E. Ikonen, I. Selek, M. Neuvonen, A. Hansen and M. Edelborg (2022). Hybrid Modelling Approach to Optimize Fouling Management in a Circulating Fluidized Bed Boiler. Fluidized bed conversion conference 2022 (FBC24), 8–11 May 2022, Gothenburg.

·        Neuvonen, M., I. Selek and E. Ikonen (2021) Estimating Fuel Characteristics from Simulated Circulating Fluidized Bed Furnace Data. Int. Conf. on Systems and Control (ICSC’21), 24-26 Nov 2021, Caen, France, 2021. (IEEE Xplore)

·        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)

·        Ikonen, E. and I. Selek (2021) Fusing Physical Process Models with Measurement Data Using FIR Calibration, Control Engineering and Applied Informatics, vol 23, nro 2., pp. 67-76. (CEAI)

·        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. 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 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   SmartFlex (2020–2022) 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:

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.

·        Hydropower dynaamic modeling, control and optimization

o   In a series of projects with PVO Vesivoima Oy, the participation to frequency control markets are considered (2019–2022) 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 (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)

·        Digital twins, artificial ingelligence and machine learning (AI/ML, IoT)

o   COGNITWIN is a Horizon 2020 SPIRE project (2019–2023), participated by e.g. SINTEF, Cybernetica, Fraunhofer and SFW. The projects looks at digital twins and their development towards cognitive properties. We apply results for fuel feed and surface fouling on-line analytics. www.cognitwin.eu. kts. M18 video.

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:

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 is developed. The role of IMSin is 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.

·        Automation in agriculture and land use

o   Vesihiisi (2021-2023) examines 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) builds the infrastruture of a single controlled subsurface drainage well.

o   PeltoSäätö pilots controlled subsurface drainage in cooperation with kpedu.

·        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   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 14 Feb 2022 / Enso

 

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