Model-based control of hydraulic heat distribution systems — Theory and application

Research output: Contribution to journalArticlepeer-review


With the share of renewable energy sources increasing in heating and hot water applications, the role of hydraulic heat distribution systems is becoming more and more important. This is due to the fact that in order to compensate for the often fluctuating behaviour of the renewables a flexible heat transfer must be ensured by these distribution systems while also taking the optimal operating conditions (mass flow, temperature) of the individual components into consideration. This demanding task can be accomplished by independently controlling the two physical quantities mass flow and temperature. However, since there exists an intrinsic nonlinear coupling between these quantities this challenge cannot be handled sufficiently by decoupled linear PI controllers which are currently state-of-the-art in the heating sector. For this reason this paper presents a model-based control strategy which allows a decoupled control of mass flow and temperature. The strategy is based on a systematic design approach from models described in this contribution, which are validated by commercially available components from which most of them can be parametrized by the data sheet. The control strategy is designed for a typical hydraulic configuration used in heating systems, which will allow the accurate tracking of the desired trajectories for mass flows, temperatures and consequently heat flows. The controllers are validated experimentally and compared to well-tuned state-of-the-art (PI) controllers in order to illustrate their superiority and prove their decoupling of the control of mass flow and temperature in real world applications.
Original languageEnglish
Article number104464
JournalControl Engineering Practice
Publication statusPublished - Aug 2020


  • Control
  • Feedforward
  • Flatness-based
  • Hydraulic
  • Hydronic
  • Model-based
  • Tracking

ASJC Scopus subject areas

  • Applied Mathematics
  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications


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