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ReLkat is co-funded by the European Fund for Regional Development [EFRE]

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Reinforcement Learning for Complex Applications of Automation Technology (ReLkat)

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Funding format: Programm zur Förderung der Forschung, Innovationen und Technologien – ProFIT

Project partners:

 

 

Goals:

  • Development of a real-time control module based on reinforcement learning (RL)
  • Enhancement for Heating, Ventilation and Air Conditioning (HVAC) in order to derive a local solution minimizing consumption of energy
  • Combination with learning of user’s behavior to add personalization
  • Minimization of overall energy cost in complex industrial production systems, development of a robust integration framework based on industrial standards like AutomationML and OPC-UA

Expected Results:

  • Establishment of RL-based framework for real-time control of IoT devices
  • Fully automatic solution for local control of HVAC tasks in smart buildings
  • Toolkit for energy-efficient control in smart factories including co-simulation
  • Validation of results in real-life smart building and smart factory applications, starting with laboratory tests

Team ReLkat

Team ReLkat at Fraunhofer IPK Berlin