| 1 | import fmpy
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| 2 | import re
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| 3 | import matplotlib.pyplot as plt
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| 4 | import numpy as np
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| 5 |
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| 6 | def getStates(model_description):
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| 7 | ''' extracts the continuous state names and their variables references from
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| 8 | a model description '''
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| 9 |
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| 10 | derivative_names = [
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| 11 | der.variable.name for der in model_description.derivatives]
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| 12 |
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| 13 | names = [
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| 14 | re.search(r'der\((.*)\)', n).group(1) for n in derivative_names]
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| 15 |
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| 16 | var_refs = get_var_refs(names, model_description)
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| 17 |
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| 18 | return (names, var_refs)
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| 19 |
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| 20 | def get_var_refs(signal_names,
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| 21 | model_description):
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| 22 | return [var.valueReference for var in model_description.modelVariables
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| 23 | if var.name in signal_names]
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| 24 |
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| 25 | ''' example model: Modelica.Blocks.Examples.PID_Controller '''
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| 26 | fmu_file = 'Modelica.Blocks.Examples.PID_Controller.fmu'
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| 27 |
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| 28 | model_description = fmpy.read_model_description(fmu_file, validate=False)
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| 29 | unzip_dir = fmpy.extract(fmu_file)
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| 30 |
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| 31 | if model_description.coSimulation is not None:
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| 32 | modelIdentifier = model_description.coSimulation.modelIdentifier
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| 33 | else:
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| 34 | modelIdentifier = model_description.modelExchange.modelIdentifier
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| 35 |
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| 36 | state_names, var_ref_states = getStates(model_description)
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| 37 |
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| 38 | ''' set up 2 FMU2Slaves from the same .fmu archive '''
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| 39 | fmus = []
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| 40 |
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| 41 | for i in range(2):
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| 42 | fmus.append(fmpy.fmi2.FMU2Slave(guid=model_description.guid,
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| 43 | unzipDirectory=unzip_dir,
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| 44 | modelIdentifier=modelIdentifier,
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| 45 | instanceName='i1')
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| 46 | )
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| 47 |
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| 48 | for fmu in fmus:
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| 49 | fmu.instantiate(loggingOn=False)
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| 50 | fmu.setupExperiment(startTime=0)
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| 51 |
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| 52 | fmu.enterInitializationMode()
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| 53 | fmu.exitInitializationMode()
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| 54 |
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| 55 | time = 0
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| 56 | n_steps = 1000
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| 57 | step_size = 1e-3
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| 58 |
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| 59 | saved_states_0 = np.zeros([n_steps, len(state_names)])
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| 60 | saved_states_1 = saved_states_0.copy()
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| 61 |
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| 62 | '''=============================================================================
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| 63 | simulation loop
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| 64 | ============================================================================='''
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| 65 |
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| 66 | for step_id in range(saved_states_0.shape[0]):
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| 67 | ''' save the state of fmu 0 '''
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| 68 | saved_states_0[step_id, :] = np.array(fmus[0].getReal(var_ref_states))
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| 69 |
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| 70 | fmus[0].doStep(currentCommunicationPoint=time,
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| 71 | communicationStepSize=step_size)
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| 72 |
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| 73 | ''' set fmu 1 state to the PREVIOUS state of fmu 0 '''
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| 74 | fmus[1].setReal(var_ref_states, saved_states_0[step_id, :])
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| 75 |
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| 76 | fmus[1].doStep(currentCommunicationPoint=time,
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| 77 | communicationStepSize=step_size)
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| 78 |
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| 79 | ''' save the state of fmu 1 '''
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| 80 | saved_states_1[step_id, :] = np.array(fmus[1].getReal(var_ref_states))
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| 81 |
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| 82 | time += step_size
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| 83 |
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| 84 | for fmu in fmus:
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| 85 | fmu.terminate()
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| 86 | fmu.freeInstance()
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| 87 |
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| 88 | fig, axes = plt.subplots(saved_states_0.shape[1], 1)
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| 89 |
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| 90 | '''=============================================================================
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| 91 | visualisation
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| 92 | ============================================================================='''
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| 93 |
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| 94 | ''' determine differences between the saved states of fmu 0 and fmu 1 '''
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| 95 | differences = saved_states_0 - saved_states_1
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| 96 |
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| 97 | for state_id, ax in enumerate(axes):
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| 98 | ax.plot(differences[:, state_id])
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| 99 | ax.set_ylabel(state_names[state_id])
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| 100 |
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| 101 | plt.show()
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