Multiple Instances of an FMU
Tutorial by Johannes Stoljar, Tobias Thummerer
🚧 This tutorial is under revision and will be replaced by an up-to-date version soon 🚧
License
# Copyright (c) 2021 Tobias Thummerer, Lars Mikelsons, Josef Kircher, Johannes Stoljar
# Licensed under the MIT license.
# See LICENSE (https://github.com/thummeto/FMI.jl/blob/main/LICENSE) file in the project root for details.Motivation
This Julia Package FMI.jl is motivated by the use of simulation models in Julia. Here the FMI specification is implemented. FMI (Functional Mock-up Interface) is a free standard (fmi-standard.org) that defines a container and an interface to exchange dynamic models using a combination of XML files, binaries and C code zipped into a single file. The user can thus use simulation models in the form of an FMU (Functional Mock-up Unit). Besides loading the FMU, the user can also set values for parameters and states and simulate the FMU both as co-simulation and model exchange simulation.
Introduction to the example
In this example we want to show that it is possible to create different instances of an FMU. The different instances can then be used to run independent simulations. After the FMU has been simulated, the simulation results are displayed in a graph. The used model is a one-dimensional spring pendulum without friction. The object-orientated structure of the SpringPendulum1D can be seen in the following graphic.
Target group
The example is primarily intended for users who work in the field of simulations. The example wants to show how simple it is to use FMUs in Julia.
Other formats
Besides, this Jupyter Notebook there is also a Julia file with the same name, which contains only the code cells and for the documentation there is a Markdown file corresponding to the notebook.
Getting started
Installation prerequisites
| Description | Command | Alternative | |
|---|---|---|---|
| 1. | Enter Package Manager via | ] | |
| 2. | Install FMI via | add FMI | add " https://github.com/ThummeTo/FMI.jl " |
| 3. | Install FMIZoo via | add FMIZoo | add " https://github.com/ThummeTo/FMIZoo.jl " |
| 4. | Install Plots via | add Plots |
Code section
To run the example, the previously installed packages must be included.
# imports
using FMI
using FMIZoo
using Plots[33m[1m┌ [22m[39m[33m[1mWarning: [22m[39mError requiring `FMIImport` from `FMIZoo`
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[33m[1m└ [22m[39m[90m@ Requires C:\Users\runneradmin\.julia\packages\Requires\1eCOK\src\require.jl:51[39mSimulation setup
Next, the start time and end time of the simulation are set. Finally, the recorded values are specified to store the results of the simulation.
tStart = 0.0
tStop = 8.0
vrs = ["mass.s"]1-element Vector{String}:
"mass.s"Import FMU
In the next lines of code the FMU model from FMIZoo.jl is loaded and the information about the FMU is shown.
# we use an FMU from the FMIZoo.jl
pathToFMU = get_model_filename("SpringPendulum1D", "Dymola", "2022x")
myFMU = loadFMU(pathToFMU)
info(myFMU)#################### Begin information for FMU ####################
Model name: SpringPendulum1D
FMI-Version: 2.0
GUID: {fc15d8c4-758b-48e6-b00e-5bf47b8b14e5}
Generation tool: Dymola Version 2022x (64-bit), 2021-10-08
Generation time: 2022-05-19T06:54:23Z
Var. naming conv.: structured
Event indicators: 0
Inputs: 0
Outputs: 0
States: 2
33554432 ["mass.s"]
33554433 ["mass.v"]
Parameters: 7
16777216 ["mass_s0"]
16777217 ["mass_v0"]
16777218 ["fixed.s0"]
16777219 ["spring.c"]
16777220 ["spring.s_rel0"]
16777221 ["mass.m"]
16777222 ["mass.L"]
Supports Co-Simulation: true
Model identifier: SpringPendulum1D
Get/Set State: true
Serialize State: true
Dir. Derivatives: true
Var. com. steps: true
Input interpol.: true
Max order out. der.: 1
Supports Model-Exchange: true
Model identifier: SpringPendulum1D
Get/Set State: true
Serialize State: true
Dir. Derivatives: true
##################### End information for FMU #####################First Instance
To create an instance of the FMU it is necessary to call the command fmi2Instantiate!(). With the component address you now have a unique instance of the FMU.
c1 = fmi2Instantiate!(myFMU; loggingOn=true)
comp1Address = c1.addr
println(c1)FMU: SpringPendulum1D
InstanceName: SpringPendulum1D
Address: Ptr{Nothing} @0x00000237583ae100
State: 0
Logging: true
FMU time: -Inf
FMU states: nothingNext, a dictionary for the parameters is created. With this dictionary you can set the initial states of the variables of the FMU. For the spring constant spring.c a value of $10.0 \frac{N}{m}$ and for the position of the mass mass.s a value of $1.0 m$ is set. The created dictionary with the specified variables for recording are passed to the command for simulation. In addition, other keywords are set. On the one hand the keyword instantiate=false is set, which prevents that in the simulation command a new instance is created. On the other hand the keyword freeInstance=false is set, this prevents that after the simulation command the instance is released.
param1 = Dict("spring.c"=>10.0, "mass_s0"=>1.0)
data1 = simulate(c1, (tStart, tStop); parameters=param1, recordValues=vrs, instantiate=false, freeInstance=false)
fig = plot(data1)<img src="data:image/png;base64,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/>
For control, you can compare again the address of the instance to the previous address, and it should be the same address. As soon as this is not the case an error would be thrown by the macro @assert.
@assert c1.addr === comp1AddressSecond Instance
To create a second instance of the FMU it is necessary to call the command fmi2Instantiate!(). With the component address you now have a unique instance of the FMU.
c2 = fmi2Instantiate!(myFMU; loggingOn=true)
comp2Address = c2.addr
println(c2)FMU: SpringPendulum1D
InstanceName: SpringPendulum1D
Address: Ptr{Nothing} @0x00000237583ad070
State: 0
Logging: true
FMU time: -Inf
FMU states: nothingThe addresses of the instantiated FMUs must differ, and you can see that in the comparison below.
@assert comp1Address !== comp2AddressAgain, a dictionary for the parameters is created. With this dictionary you can set the initial states of the variables of the FMU. For the spring constant spring.c a value of $1.0 \frac{N}{m}$ and for the position of the mass mass.s a value of $2.0 m$ is set. The created dictionary with the specified variables for recording are passed to the command for simulation. As before, the two keywords instantiate=false and freeInstance=false are set.
param2 = Dict("spring.c"=>1.0, "mass.s"=>2.0)
data2 = simulateCS(c2, (tStart, tStop); parameters=param2, recordValues=vrs, instantiate=false, freeInstance=false)
plot!(fig, data2)<img src="data:image/png;base64,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" />
For control, you can compare again the address of the instance comp2 to the previous address comp2Address and it should be the same address.
@assert c2.addr === comp2AddressUnload FMU
After plotting the data, the FMU is unloaded and all unpacked data on disc is removed.
unloadFMU(myFMU)Summary
Based on the example it can be seen that it is possible to create different instances of an FMU. The different instances can then be used to perform different simulations.