DE | EN
Home
About Us
Overview
Facts and Figures
Organization
Scientists
Contact
Approach
Situations offered
Research
Overview
Application Fields
Projects
Publications
Scientists
Preprints
Institutional Cooperation
Archiv 02-14
Transfer
Overview
Industry
References
MODAL-AG
Spin Offs
Software
Patents
Schools
Overview
MathInside
MATHEATHLON
Matheon-Kalender
What'sMath
Training for Teachers
Summer Schools
Events
Press
Overview
Releases
News
Overview
Matheon Head
Number of the week
News 2002 - 2014
Activities
Overview
Workshops
15 Years Matheon
Media
Overview
Photos
Videos
Audios
Booklets
Books
News from around the world

Dr. Carlos Rautenberg

carlos.rautenberg@math.hu-berlin.de


Projects as a project leader

  • SE19

    Optimal Network Sensor Placement for Energy Efficiency

    Dr. Carlos Rautenberg

    Project heads: Dr. Carlos Rautenberg
    Project members: Dr. Andrea N. Ceretani
    Duration: 01.06.2017 - 31.12.2018
    Status: running
    Located at: Humboldt Universität Berlin

    Description

    The estimation of the temperature and airflow distribution in buildings via the location of sensor networks is a nonlinear and multiscale problem where dynamics and measurements are (in general) stochastically perturbed. The goal here is to reliably outline temperature and airflow in certain areas by placing sensors on prescribed admissible locations while optimizing several criteria. A trustworthy estimation, provided that closed-loop controllers are in place, becomes a main step in reducing the energy consumption of such control systems.

    http://www2.mathematik.hu-berlin.de/~rautenca/SE19.htm
  • SE15

    Optimal Network Sensor Placement for Energy Efficiency

    Dr. Carlos Rautenberg

    Project heads: Dr. Carlos Rautenberg
    Project members: -
    Duration: 01.06.2014 - 31.05.2017
    Status: completed
    Located at: Humboldt Universität Berlin

    Description

    The optimal sensor placement problem for the estimation of the temperature distribution in buildings is a highly nonlinear and multi-scale problem where stochastic perturbations are usually present. The main goal here is to properly locate sensors in order to reliably estimate the temperature distribution in certain areas. Since feedback controllers are usually in use, a proper estimation of the state is of utmost importance in order to reduce energy consumption of such controllers.

    http://www2.mathematik.hu-berlin.de/~rautenca/SE15.htm