IDEAS home Printed from
   My bibliography  Save this article

Soft-constrained robust model predictive control of a plate heat exchanger: Experimental analysis


  • Oravec, Juraj
  • Bakošová, Monika
  • Galčíková, Lenka
  • Slávik, Michal
  • Horváthová, Michaela
  • Mészáros, Alajos


Real processes with heat exchange have usually complex behaviour and are energy intensive. In practical applications, the process variables are always bounded, and it is suitable to include these boundaries into the controller design. The soft-constrained robust model predictive controller has been designed to improve the control performance and energy consumption in comparison with the robust model predictive control with only hard constraints. Experimental application of soft-constrained robust model predictive control (SCR MPC) for a laboratory plate heat exchanger is presented in this paper. The plate heat exchanger is a non-linear process with asymmetric dynamics and is modelled as a system with parametric uncertainties. The controlled variable is the temperature of the heated fluid at the outlet of the heat exchanger and the manipulated variable is the volumetric flow rate of the heating fluid. The actuator is a peristaltic pump and the influence of the linear and non-linear actuator characteristics on the control performance is also investigated. The set-point tracking using SCR MPC is studied for the laboratory plate heat exchanger in an extensive case study. The experimental results confirmed the improvement of the control responses and reduction of energy consumption by introducing the soft constraints into MPC design.

Suggested Citation

  • Oravec, Juraj & Bakošová, Monika & Galčíková, Lenka & Slávik, Michal & Horváthová, Michaela & Mészáros, Alajos, 2019. "Soft-constrained robust model predictive control of a plate heat exchanger: Experimental analysis," Energy, Elsevier, vol. 180(C), pages 303-314.
  • Handle: RePEc:eee:energy:v:180:y:2019:i:c:p:303-314
    DOI: 10.1016/

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Dong, Zhe & Zhang, Zuoyi & Dong, Yujie & Huang, Xiaojin, 2018. "Multi-layer perception based model predictive control for the thermal power of nuclear superheated-steam supply systems," Energy, Elsevier, vol. 151(C), pages 116-125.
    2. Pospíšil, Jiří & Špiláček, Michal & Kudela, Libor, 2018. "Potential of predictive control for improvement of seasonal coefficient of performance of air source heat pump in Central European climate zone," Energy, Elsevier, vol. 154(C), pages 415-423.
    3. Oravec, Juraj & Bakošová, Monika & Trafczynski, Marian & Vasičkaninová, Anna & Mészáros, Alajos & Markowski, Mariusz, 2018. "Robust model predictive control and PID control of shell-and-tube heat exchangers," Energy, Elsevier, vol. 159(C), pages 1-10.
    4. Zhang, Pan & Ma, Ting & Li, Wei-Dong & Ma, Guang-Yu & Wang, Qiu-Wang, 2018. "Design and optimization of a novel high temperature heat exchanger for waste heat cascade recovery from exhaust flue gases," Energy, Elsevier, vol. 160(C), pages 3-18.
    5. Yang, Tingting & Wang, Wei & Zeng, Deliang & Liu, Jizhen & Cui, Can, 2017. "Closed-loop optimization control on fan speed of air-cooled steam condenser units for energy saving and rapid load regulation," Energy, Elsevier, vol. 135(C), pages 394-404.
    6. Ponce, Carolina V. & Sáez, Doris & Bordons, Carlos & Núñez, Alfredo, 2016. "Dynamic simulator and model predictive control of an integrated solar combined cycle plant," Energy, Elsevier, vol. 109(C), pages 974-986.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Oravec, Juraj & Horváthová, Michaela & Bakošová, Monika, 2020. "Energy efficient convex-lifting-based robust control of a heat exchanger," Energy, Elsevier, vol. 201(C).


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:180:y:2019:i:c:p:303-314. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Haili He). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.