JModelica.org 1.6 released

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jakesson
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JModelica.org 1.6 released

We are pleased to announce that JModelica.org 1.6 is now available for download.
Highlights in JModelica.org 1.6

  • Derivative-free optimization of FMUs for parameter tuning
  • Index reduction to handle high-index DAEs
  • A pseudo spectral optimization algorithm
  • A graphical user interface for visualization of simulation and optimization results

The derivative-free optimization algorithm in JModelica.org enables users to calibrate dynamic models compliant with the Functional Mock-up Interface standard (FMUs) using measurement data. The new functionality offers flexible and easy to use Python functions for model calibration and relies on the FMU simulation capabilities of JModelica.org. FMU models generated by JModelica.org or other FMI-compliant tools such as AMESim, Dymola, or SimulationX can be calibrated.

Pseudo spectral optimization methods, based on collocation, are now available. The algorithms relies on CasADi for evaluation of derivatives, first and second order, and IPOPT is used to solve the resulting non-linear program. Optimization of ordinary differential equations and multi-phase problems are supported. The algorithm has been developed in collaboration with Mitsubishi Electric Research Lab, Boston, USA, where it has been used to solve satellite navigation problems.

A Python-based graphical user interface for easy visualization of simulation and optimization results is a new addition to JModelica.org. This is a feature has been frequently requested by users and we are therefore very pleased with this development.
For additional information, see the release notes. A binary installer for Windows is available at the download page.