Conference article

Discrete-time models for control applications with FMI

Rüdiger Franke
ABB AG, Mannheim, Germany

Sven Erik Mattsson
Dassault Systèmes AB, Lund, Sweden

Martin Otter
DLR, Institute of System Dynamics and Control, Germany

Karl Wernersson
Dassault Systèmes AB, Lund, Sweden

Hans Olsson
Dassault Systèmes AB, Lund, Sweden

Lennart Ochel
Department of Computer and Information Science, Software and Systems, Linköping University, Sweden

Torsten Blochwitz
ESI ITI GmbH, Dreseden, Germany

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Published in: Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017

Linköping Electronic Conference Proceedings 132:57, p. 507-515

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Published: 2017-07-04

ISBN: 978-91-7685-575-1

ISSN: 1650-3686 (print), 1650-3740 (online)


The paper proposes an extension of FMI 2.0 for the rigorous treatment of discrete-time models. This includes the introduction of discrete-time states, the declaration of clocks in the model description and an extension of the calling interface for the external activation of clocks by an importing environment.
The synchronous discrete-time extension enables for the first time the synchronization of FMUs with the environment and with other FMUs. It specializes the existing generic event mechanism of FMI 2.0 and maps to synchronous features of Modelica.
Discrete-time FMUs are needed for the generation of controller code from functional models. This paper outlines different use cases, including a simple PI controller, feed forward control with a nonlinear inverse model and nonlinear model predictive control.
The FMI change proposal FCP-001 and the Modelica change proposal MCP-0024 describe the proposed extensions in more detail. Test implementations exist in the simulation tools Dymola and OpenModelica and in the importing optimization solver HQP. The use cases given in this paper served for further refinement of the change proposals and the test implementations.


Modelica, Synchonous modeling, Inline Integration, Modelica, Synchonous modeling, Inline Integration, Model-based Control, Nonlinear Inverse Model, Feed Forward Control, NMPC


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