IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i24p8578-d706466.html
   My bibliography  Save this article

Smart Modulation for Control Systems with High Regulation Capabilities for Cooling Systems Optimisation and Carbon Footprint Reduction in Industry

Author

Listed:
  • Roman Baraniuk

    (Institute for Machine Tools and Production Processes IWP, Chemnitz University of Technology, 09126 Chemnitz, Germany)

  • Welf-Guntram Drossel

    (Institute for Machine Tools and Production Processes IWP, Chemnitz University of Technology, 09126 Chemnitz, Germany
    Fraunhofer Institute for Machine Tools and Forming Technology IWU, 09126 Chemnitz, Germany)

Abstract

Nowadays, every large enterprise is concerned about reducing CO 2 emissions. Along with legislation, management, packaging, and transportation decisions, optimising the operation of automated systems in the industry is important. Overheating processes or large cooling systems of one machine during product assembly may seem minor but at the industry level it is quite significant. Either an optimisation of cooling systems or an intelligent machine control which will prevent heat strokes and allow the transition to passive cooling of the whole system is an important issue for improving machine tools efficiency and contributing therefore to CO 2 reduction in the industry sector. This research is a transitional phase from the creation of a control system to solve the problems of resonance in the control of systems with parallel piezo kinematics, which were designed to automate the iterative process of non-circular drilling with a precise shape and the subsequent research on the implementation of smart control to optimise the cooling of industrial machines. The total dynamics of the example system in this research is unknown and consists of the dynamics of electrical converters, piezo kinematics, and mechanics. The control signal of this system is generated by the model of the system state with assumptions and simplifications in combination with machine learning techniques considering the previous errors of the transient characteristics with the possibility of re-drilling without damaging the workpiece and with possibility of further trainings to eliminate the iterative process in general. Algorithms for further training at different resonances with a drilling depth change for cylinders of internal combustion engines are offered. These algorithms are proposed for accurate transmission of the input signal amplitude even in resonant situations, power optimisation, increase the system efficiency, as well as reducing the carbon footprint when used in industry in specific applications.

Suggested Citation

  • Roman Baraniuk & Welf-Guntram Drossel, 2021. "Smart Modulation for Control Systems with High Regulation Capabilities for Cooling Systems Optimisation and Carbon Footprint Reduction in Industry," Energies, MDPI, vol. 14(24), pages 1-14, December.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8578-:d:706466
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/24/8578/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/24/8578/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Lorena Espina-Romero & José Gregorio Noroño Sánchez & Humberto Gutiérrez Hurtado & Helga Dworaczek Conde & Yessenia Solier Castro & Luz Emérita Cervera Cajo & Jose Rio Corredoira, 2023. "Which Industrial Sectors Are Affected by Artificial Intelligence? A Bibliometric Analysis of Trends and Perspectives," Sustainability, MDPI, vol. 15(16), pages 1-18, August.

    Corrections

    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:gam:jeners:v:14:y:2021:i:24:p:8578-:d:706466. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.