WORKSHOP 1
CO-SIMULATION
ADM711, Workshop 1, January 2013
Copyright 2013 MSC.Software Corporation
ML WS1 - 1
ADM711, Workshop 1, January 2013
Copyright 2013 MSC.Software Corporation
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Getting started
Start Adams/View:
a.
b.
c.
d.
e.
f.
Click on Existing model
Click on browser for
specifying working
directory .
Select folder containing
mod1_cosim relative to
Adams/Controls training
files on your computer.
Click OK.
Click on the browser for
specifying the file name.
In file name select
spring_damper.cmd
and Click OK.
a
c
d
e
b
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Copyright 2013 MSC.Software Corporation
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f
Investigate the Model
a
Investigate the current model by
simulating for a short time:
a. Run a dynamic simulation
for 2 seconds, 100 steps.
b. Note that the Adams-only
spring-damper system
oscillates.
c. The other spring damper
system in the model simply
falls down.
d. Right-click on the springdamper element named
‘adams_spring_force’ and
note the K and C values for
the spring element in
Adams:
e. K = _________
f. C = _________
ADM711, Workshop 1, January 2013
Copyright 2013 MSC.Software Corporation
c
b
e
f
ML WS1 - 4
d
Create State VARIABLE, Integrate with Model
To build a State Variable to be
passed in from MATLAB:
Create a new Variable using the
menu picks:
a. Click on Elements.
b. Create State Variable
defined by algebraic
equation.
c. Enter force_matlab for
the Name.
d. Specify 0.0 as the
function value (this will be
over-written during cosimulation).
e. Click OK.
Modify the model so that the
Variable is used by the
SFORCE element:
f.
g.
Adams/Controls requires State Variables for
communication with MATLAB or EASY5. The model
currently lacks a State Variable representing the spring
force that is to be calculated by MATLAB.
b
a
c
d
e
f
Modify the SFORCE
named ‘SFORCE_1’.
Use the VARVAL()
function to reference the
new state VARIABLE, for
example:
VARVAL(force_matlab)
ADM711, Workshop 1, January 2013
Copyright 2013 MSC.Software Corporation
g
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Export the Plant
Simulate the model again, verify that the ball simply drops since
the Variable (and hence the SFORCE) has a zero-value. During
co-simulation, the Variable (and hence the SFORCE) will be
constantly updated, so the behavior will be different.
Create files required by
MATLAB for co-simulation by
selecting the menu picks:
a. Controls: Plant
Export
In the resulting dialog box,
specify the following:
b. File Prefix: cosim
c. Input Signal(s):
force_matlab
d. Output Signal(s):
(use Browse and
select in the exact
order as shown):
- displ_part_2
- displ_part_3
- vel_part_2
- vel_part_3
e. Target Software:
MATLAB
f. Leave all other
settings as default
g. Click OK.
a
b
c
d
Verify that files named:
-cosim.m
-cosim.adm
-cosim.cmd
have been created in the working
directory of Adams/View.
e
f
ADM711, Workshop 1, January 2013
Copyright 2013 MSC.Software Corporation
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Setup in MATLAB
Start MATLAB and:
a. Change the working directory
of MATLAB to be where your
cosim.m file exists.
b. Enter cosim in the MATLAB
shell to execute the cosim.m
file.
Create a Simulink block that
represents the Adams component by :
c. Enter the command,
adams_sys into the MATLAB
shell.
The steps above create a blank
‘adams_sub’ Simulink block which
represents your Adams model.
At this point, a Simulink model can be built around the adams_sub
block using the inputs and outputs that have been defined for the
adams_sub block. Note that the inputs and outputs correspond to
what was specified during the plant export process in Adams.
ADM711, Workshop 1, January 2013
Copyright 2013 MSC.Software Corporation
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Load an Existing Simulink Model
Rather than create a new Simulink
model to interact with the Adams block,
an existing model can be loaded that
will make use of the adams_sub block
created earlier.
Load an existing Simulink model
containing the spring-damper
modeled in MATLAB:
a. Enter the following
command in the
MATLAB command line:
matlab_spring_start
This command will open
the file
‘matlab_spring_start.mdl
’ from the working
directory.
b. The adams_sub block
can now be dragged
from the initial Simulink
model into the model
above.
ADM711, Workshop 1, January 2013
Copyright 2013 MSC.Software Corporation
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Setup and Co-simulation
Before simulation, ensure that the
adams_sub block has the appropriate
parameters. Double-click the adams_sub
block, then the Adams plant block to view
the block parameters.
In the Adams plant mask settings, modify the
following parameters:
– Communication Interval = 0.005 (default)
– Output files prefix = ‘cosim_005’ (include
single-quotation marks)
– Leave all other settings as default, then save
the Simulink model.
Specify an end-time of 2 seconds for the simulation
by using the menu picks:
•
Simulation: Configuration Parameters
•
Click the ‘play’ button in the MATLAB to
simulate the Simulink Model.
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Inspect Simulation Results
Inspect the results:
a. Double-click the scope blocks
in MATLAB and inspect the
displacement and velocity
values.
b. The displacement scope will
plot the position of the ball for
the Adams-calculated force in
the model (the upper trace)
and the MATLAB-calculated
force in the model (the lower
trace).
Note how the MATLAB-calculated force does not have the same
damping behavior as the Adams-calculated force.
ADM711, Workshop 1, January 2013
Copyright 2013 MSC.Software Corporation
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Repeat Simulation
Repeat the co-simulation with a finer
sampling interval:
– Communication Interval = 0.001
– Output files prefix = ‘cosim_001’
– Inspect the displacement and
velocity plots.
– Repeat with smaller sampling rates
and investigate the effect on
displacement and velocity. The
effect of sampling rate is shown for
two co-simulations with rates of
0.001 and 0.0001 seconds. These
plots use the scope value
‘Displacement Difference’ found in
the model.
ADM711, Workshop 1, January 2013
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Algebraic Loops, Artificial Dynamics
•
The current model contains an ‘Artificial Lag’ block (a Transfer Function that
acts as a filter) in order to break any algebraic loops in MATLAB. MATLAB
attempts to resolve algebraic loops through an iterative process; this can be
seen when the inputs to Adams, as shown in the .msg file, are repeated
several times. Algebraic loops in the MATLAB model will slow simulations
down and possibly cause wrong answers.
•
Inserting a simple dynamic element (such as a filter block) into the loop will
resolve the problem. Note that very few dynamic systems can be modeled
as not having dynamics such as lag, so this is likely a realistic feature to
build into a model.
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