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Nonlinear model predictive control in modelica using FMI and optimization library

Published: 18 April 2016 Publication History

Abstract

In this work-in-progress paper, a currently ongoing development of a generic tool for nonlinear model predictive control is presented. By using an extended interface of FMI 2.0, it is possible to simulate a model that acts as prediction model while the actual system is simulated simultaneously. A trajectory optimization that uses the prediction model provides optimized input control values for the actual system at every sample time. The current work is based on the Optimization library for Dymola and an extended version of FMI 2.0 Co-Simulation.
The structure of this approach is explained in detail as well as possible settings and limitations. An example shows the practicability and an outlook for further development is given.

References

[1]
J. Brembeck, A. Pfeiffer, M. Fleps-Dezasse, M. Otter, K. Wernersson, and H. Elmqvist. Nonlinear State Estimation with an Extended FMI 2.0 Co-Simulation Interface. In Proceedings of the 10th International Modelica Conference, pages 53--62, Lund, Sweden, Mar. 2014. Linköping University Electronic Press.
[2]
E. F. Camacho and C. B. Alba. Model predictive control. Springer Science & Business Media, 2013.
[3]
P.-O. Larsson, F. Casella, F. Magnusson, J. Andersson, M. Diehl, and J. Åkesson. A Framework for Nonlinear Model-Predictive Control Using Object-Oriented Modeling with a Case Study in Power Plant Start-Up. In IEEE Conference on Computer Aided Control System Design (CACSD), 2013, pages 346--351. IEEE, 2013.
[4]
Modelica Association. FMI for Model Exchange and Co-Simulation 2.0, July 2014, https://www.fmi-standard.org/.
[5]
A. Pfeiffer. Optimization Library for Interactive Multi-Criteria Optimization Tasks. In 9th International Modelica Conference, pages 669--679, Munich, Germany, Sep. 2012.
[6]
F. Rüdiger, M. Walther, N. Worschech, W. Braun, and B. Bachmann. Model-based Control with FMI and a C++ runtime for Modelica. In 11th International Modelica Conference, pages 339--347, Versailles, France, Sep 2015.

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  • (2021)Advanced Controller Development Based on eFMI with Applications to Automotive Vertical Dynamics ControlActuators10.3390/act1011030110:11(301)Online publication date: 12-Nov-2021
  1. Nonlinear model predictive control in modelica using FMI and optimization library

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      cover image ACM Other conferences
      EOOLT '16: Proceedings of the 7th International Workshop on Equation-Based Object-Oriented Modeling Languages and Tools
      April 2016
      75 pages
      ISBN:9781450342025
      DOI:10.1145/2904081
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 18 April 2016

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      Author Tags

      1. FMI
      2. FMU
      3. co-simulation
      4. modelica
      5. nonlinear model predictive control
      6. optimization

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      EOOLT '16 Paper Acceptance Rate 10 of 11 submissions, 91%;
      Overall Acceptance Rate 10 of 11 submissions, 91%

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      • (2021)Advanced Controller Development Based on eFMI with Applications to Automotive Vertical Dynamics ControlActuators10.3390/act1011030110:11(301)Online publication date: 12-Nov-2021

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