Research License — FMIEstimationDemo

Functional Mockup Interface Estimation Demo for providing an example of state estimation for nonlinear systems using Modelica and the functional mockup interface.

This software demonstrates the use of the Functional Mockup Interface (FMI) to construct extended Kalman filters (EKF) and ensemble Kalman filters (EnKF) for state estimation in Modelica using the Dymola compiler.

One of the key advantages of Modelica is that it enables users to create large-scale physical system models via the interconnection of simpler subsystem or component models, and thereby manage the complexity inherent in describing these large systems. While one candidate use for such models is in using data to estimate unmeasured variables of a complex system, the equation compilation process can make it difficult to work with the state vector directly when implementing state estimation methods. Functional mockup units (FMUs), generated via FMI, can address this limitation because they provide a means for accessing and modifying the state vector during simulation. This small software package provides two examples demonstrating the implementation of an EKF and EnKF by combining Modelica models and FMUs on a four state model of a permanent magnet synchronous motor, as described in detail in the accompanying publication. Though the size of this example is somewhat limited, this approach has been found to scale to much larger problems.

  •  Laughman, C.R., Bortoff, S.A., "Nonlinear State Estimation with FMI: Tutorial and Applications", American Modelica Conference 2020, March 2020.
    BibTeX TR2020-031 PDF Software
    • @inproceedings{Laughman2020mar,
    • author = {Laughman, Christopher R. and Bortoff, Scott A.},
    • title = {Nonlinear State Estimation with FMI: Tutorial and Applications},
    • booktitle = {American Modelica Conference 2020},
    • year = 2020,
    • month = mar,
    • url = {https://www.merl.com/publications/TR2020-031}
    • }

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