Multi-Disciplinary Senior Design Conference
Kate Gleason College of Engineering
Rochester Institute of Technology
Rochester, New York 14623
Project Number: P10029
PROCESS DEVELOPMENT FOR SIMULATING AND
CONTROLLING BIOMIMETIC SYSTEMS
Zachary Wessner (M.E.) Project Manager
Alex Bean (I.S.E.)
Jaclyn Tylkowski (M.E.) Lead Engineer
Tuan Tran (E.E.)
Kevin Mudrak (M.E.)
Mark Wood (M.E.)
SoftMotion: National Instruments software package
that allows integration of LabVIEW and SolidWorks.
ABSTRACT
The goal of this project was to develop a process for
simulation and closed loop control of an air muscle
actuated biomimetic system. A multidisciplinary team
of engineers were brought together to design,
physically and virtually, and to form a controls
system. The initial stage of development began with a
representation of the air muscles assembly in
SolidWorks. Through the application of LabVIEW
SoftMotion software, motor profiles can be added to
the model to simulate the motion of air muscles. The
final design included a universal control system to
inflate and deflate the air muscles and at the same time
record the displacement based on data acquired from
linear potentiometers.
A controls program was
designed to collect data which allows future teams to
obtain air muscle motion profiles for input into the
LabVIEW SoftMotion motor profiles.
NOMENCLATURE
Air Muscle: A mechanical device which contracts and
extends through the use of pressurized air.
Biomimetic: The act of mimicking biology through
engineering technology.
Degree of Freedom: A direction of motion.
SolidWorks: 3-Dimensional modeling software
LabVIEW: Drag and drop programming environment
INTRODUCTION
The objective of this project was to develop a process
for simulation and closed-loop control of an air muscle
actuated biomimetic system. Previous projects within
Rochester Institute of Technology’s biomedical
engineering
track
have
explored
initial
characterization of air muscles, constructed various
biomimetic prototypes representing the human hand
and elbow, and developed multiple open-loop controls
programs.
Past teams have been using a trial and error method for
developing and designing their systems. This means
that each team must physically prototype their device
prior to knowing whether it functions and how well it
performs. To undergo this process, means investing
significant build time and cost. The idea of being able
to prototype and test their devices virtually before
physical construction would save development time
and associated costs. Therefore, our project explored
and experimented with virtual simulation using
LabVIEW NI SoftMotion coupled with SolidWorks
2009 Premium to provide users with a three
dimensional, controllable virtual prototype.
After developing a virtual prototype, it was desired to
input actual air muscle response curves into the
program to simulate how the actual system will
Copyright © 2010 Rochester Institute of Technology
Proceedings of the Multi-Disciplinary Senior Design Conference
behave. Not having velocity or force curves readily
available led us into our own characterization of a
variety of air muscles. A physical system was
constructed to represent the same model as the virtual
prototype. A universal, expandable perspective was
employed when designing the controls box which
powered our physical prototype. The reason for this
was that each previous team built their own control
boxes, each being almost identical, and specific to
their tasks. Therefore, it was deemed worthwhile to
promote continuity among future projects by
providing them with an already assembled controls
box with detailed wiring diagram and controls
programming.
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Virtual Prototyping
New for 2009, LabVIEW NI SoftMotion was coupled
with SolidWorks Premium to create a virtual
prototyping platform. SoftMotion enables virtual
simulation for various motion applications by
controlling models created in SolidWorks using NI
SoftMotion function blocks. The benefit of this is that
one can evaluate different designs prior to incurring
the cost of physical prototypes. Being a brand new
software package, operational knowledge was minimal
and hard to find. After experimenting with the
software and going through tutorials available online
from LabVIEW’s website, the team was able to
achieve motion from the virtual model.
A variety of air muscles were tested in order to obtain
an increased understanding of the effects each
parameter plays in the actuator’s response. The
parameters that were varied included operating
pressure and initial deflated length of the air muscle.
A closed-loop controls program was developed which
carried out the testing procedure automatically for all
80 trials. This data was then compiled for analysis and
to input into the virtual simulation.
PROCESS
Design Initiative
The overall design initiative focused around
developing an antagonistic pair of air muscles which
would actuate a one degree of freedom (DOF) system
with a certain level of fidelity. This system was
considered a constant throughout the project and as
such was used in both the virtual and physical
prototyping phases.
The antagonistic pair functions much like a human set
of muscles. As one muscle contracts the other relaxes
or vents air in this case, causing a pulling force in the
direction of the contracted muscle. This motion then
can be reversed by venting the already inflated muscle
and filling the relaxed muscle.
In order to accurately control the position of the
system, linear slide potentiometers were used for
closed-loop feedback tracking of the air muscle
position, which could then be related to the rotary
position of the joint. It was decided to experiment
using this potentiometer setup versus a rotary mount
due to the goal of eventually scaling these devices
down for microsurgical applications. To attach a
rotary potentiometer directly to the joint would
negatively impact the scalability of the device.
Figure 2: Virtual model from SolidWorks screenshot.
The goal for the virtual simulation was to accurately
model the device in SolidWorks then to apply air
muscle actuator profiles to the device and observe its
virtual response.
Not having air muscle
characterization curves readily available, it was
decided to go ahead and set velocity and acceleration
as constants for this initial simulation. SoftMotion’s
Straight Line Move function block was used to control
the SolidWorks model through use of virtual motors
and axes.
Project P10029
Proceedings of the Multi-Disciplinary Senior Design Conference
Page 3
switch the focus from the virtual simulation to
obtaining accurate and reliable velocity curves for a
variety of air muscles.
Figure 3: SoftMotion Straight Line Move function
block.
Air Muscle Characterization
In order to empirically obtain velocity and
displacement data for a variety of air muscles, a
physical system needed to be created. With a budget
of zero, the team utilized already available parts from
previous projects to construct this prototype. After
reviewing previous projects, it was observed that each
team constructed their own controls box specific for
their prototypes and that continuity was lacking
between the projects. Therefore it was decided that
since a physical prototype must be constructed, we
would develop it for expandability and make a
universal controls box that could be connected to
many prototypes.
A front panel was created in LabVIEW in which the
user would input the desired position, in degrees, for
the one degree of freedom joint to actuate to. After
selecting run, the system would actuate until the
desired value on the virtual sensor was reached. The
indicator lights would signal a completed movement,
and if any errors occurred they would be displayed in
the error message box.
Figure 5: Universal Control Box
Figure 4: Virtual Simulation front panel screenshot.
The software allows for tracking of many variables of
the systems response. For our initial simulation we
focused on tracking the systems velocity and
displacement, through use of graphs and a visual
tracing feature. As mentioned previously, to be able to
actually observe realistic virtual actuation it is
necessary to obtain the velocity curves of a similar
physical system. These curves would then be used to
generate functions, which could be programmed into
the virtual controls to provide a realistic simulation for
future teams to use. Therefore, it was decided to
The main components of the controls box are the relay
board, a regulator, the fill valve set, the vent valve set,
and a data acquisition unit (DAQ). The external
connections to the controls box include three 120VAC
power cords, an air supply, fill and vent tubing to the
prototype muscles, and the potentiometer signals. The
relay board receives the command from the computer
to open or close the valves, which therefore inflates or
deflates the air muscles. Once the air muscles are
inflated or deflated the use of linear slide
potentiometers tracks the displacement of each
muscle. The DAQ is an Analog-to-Digital Converter
(ADC) that takes the analog feedback signals from the
linear potentiometers and converts them to digital
inputs for the LabVIEW program to check for
positional accuracy. The controls box utilizes a
parallel connector to be used for attaching various
potentiometer setups or other prototypes. A detailed
wiring diagram was made for future users to
troubleshoot the system or to expand upon it.
Copyright © 2008 Rochester Institute of Technology
Proceedings of the Multi-Disciplinary Senior Design Conference
Page 4
on the LabVIEW front panel to input the desired
position. The fourth operating mode, Vent All, is used
to open all of the vent valves to release the air from the
system. The front panel also displays a real-time
velocity histogram of the system.
Figure 6: Physical prototype including the air muscles
and linear potentiometer.
The physical system was constructed based off the
original design initiative of an antagonistic pair of air
muscles actuating a single degree of freedom joint.
The potentiometers were mounted as shown in Figure
6 which tracked the air muscle positions directly. The
rotary motion of the joint was preloaded with a one
pound mass to prevent unnecessary slack in the
strings. It was desired to test a variety of air muscles
to determine the effects of varying operating pressure
and initial air muscle length. An 80 trial test plan was
developed in which four different air muscle lengths
and four different operating pressures were tested.
The deflated air muscle lengths tested were 12, 10, 8,
and 6 inches. The system operating pressure was
regulated to 70, 60, 50, and 40 psi. In order to adjust
the air muscle length without permanently altering our
test sample, hose clamps were used to restrict or pinch
off air flow to certain lengths of the air muscle. The
use of mesh, latex tubing, and plastic end pieces were
considered constant for all muscles used. This paper
will not go into details on air muscle construction,
since it has already been explained in depth by
previous teams.
Figure 7: Restriction of air by clamping the air muscle.
A closed-loop controls program was constructed to
operate the system, again with expandability and
adaptability in mind. The controls system was
designed in LabVIEW with four different modes the
user can select from. The first mode, Joystick, uses an
external potentiometer to control the desired position
of the system. The second mode, Test Sequence,
allows the user to pre-program their desired testing
scenario and it will carry out the procedure for them.
The third mode, Virtual Joystick, uses a slider control
Figure 8: Test Sequence mode of controls program.
Need to update screenshot on Wednesday
For our air muscle characterization, the Test Sequence
mode was utilized. The system was pre-programmed
to actuate at 0 volts for 5 seconds then actuate to 10
volts or as close as it can get for 5 seconds, and then
finally back to 0 volts for another 5 seconds. After the
last move has completed the program prompts the user
with a save as dialog box, in which the user can
specify a location to save the testing results. The
program is set to export time, desired position, and
actual position to a Microsoft Excel file once the test
sequence has completed. In addition, the first row of
the file includes the operating pressure, air muscle
length, and trial number for the test that was just
performed.
Theoretical Actuation Force Modeling
When designing a system or device it is advantageous
to understand what level of force the actuator will
provide and what are the specifications of an air
muscle that can provide this force. In addition to
virtually prototyping a system, our team decided to
develop a MATLAB program which calculated the
theoretical force of an air muscle actuator for various
parameters such as operating pressure (P), deflated
length (l), inflated length (δl), deflated radius (r), and
inflated radius (δr) of the air muscle shown in Figure
9. With these values the theoretical force can be
determined.
Project P10029
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Proceedings of the Multi-Disciplinary Senior Design Conference
+δr
P
F
r
δl
custom actuation profiles, collision detection, and
virtual sensors were identified; however empirical
investigation of air muscle motion properties were
required beforehand.
l
Figure 9: Model of air muscle [1].
The resulting force can be found from the sum work
done longitudinally and axially.
δWlongitudinalpressure+δWaxialpressure+δWequilibrium= 0
(1)[2]
Equation (1) can be simplified as the following
equation:
2πrlP(δr)+πr2P(-δl)-F(δl)= 0
Then solving for F leads to:
(2)
Theoretical Force Model
The MATLAB program is written based on a 12 inch
air muscle assuming that the length, pressure, and
radius vary linearly. The user inputs the inflated
length and radius, the initial length and radius, and the
operating pressure.
Subsequently, the program
outputs a theoretical maximum force value. The
program then varies the length, pressure, and radius
linearly and independently from one another to obtain
3 theoretical force curves. These three curves are then
overlaid to compare the effects of length, pressure, and
radius of force output.
Air Muscle Characterization
Plot 40PSI 6 Inch
2.5

2rlPr
 r 2P
l
(3)1
Equation 3 was used as the basis for the MATLAB
program. It prompts the user for the necessary
variables and returns the theoretical force. It has been
determined that empirical testing to discover the
relationship between the rate of change of the radius,
length, and pressure needs to occur in order to advance
the usefulness of our model. If future teams were to
find these relationships, the program could then output
the entire force trace for a given air muscle. This
information combined with the empirical testing to
provide SoftMotion with realistic actuation profiles
would allow future users to accurately virtually
simulate a device and determine which actuator
specifications to use for a particular application.
RESULTS AND DISCUSSION
Virtual Prototyping
After creating a SolidWorks assembly and a VI
utilizing the Softmotion package in LabVIEW, it was
possible to run the SolidWorks assembly with this
LabVIEW program. The program allowed the user to
input a desired angle for the finger to move to. This
was accomplished through the straight line move
function from the Softmotion package. By converting
this angle to a linear movement, it was possible to use
a second straight line move to visually see the
potentiometers move with respect to the finger
movement. This imitated the air muscles pulling on
the potentiometers to move the finger. We were not
able to use the Softmotion VI to run the physical
prototype, due to insufficient LabVIEW hardware.
Advanced capabilities within the software such as
2
1.5
Amplitude
F
1
0.5
0
-0.5
0
20
40
60
80
100
120
Time (tenths of seconds
140
160
180
Figure 10: Comparison plot showing the empirical test
data and the simulated transfer function.
System order reduction approximation was used for
creating the transfer function for each test scenario.
By approximating the system as a first order system
the time constant of the system, would be 63% of
the final value. Since the input was pressure and the
feedback was voltage, which both varied by an order
of magnitude from each other, the pressure was
reduced by a factor of 10 and used as an approximated
step input. For example, 70 psi would be a step input
of 7, which was used to keep the gain closer to 1.
MATLAB SimuLink was used to validate the transfer
functions by comparing it to the empirical curves. The
plots of the empirical data versus the simulated
response show very little variation.
Copyright © 2008 Rochester Institute of Technology
Proceedings of the Multi-Disciplinary Senior Design Conference
CONCLUSIONS AND RECOMMENDATIONS
In conclusion the project successfully controlled an
antagonistic pair of air muscles using closed-loop
feedback. Furthermore, the team also benchmarked
and investigated LabView SoftMotion, for virtual
prototyping, and determined with the lack of available
information, other software packages should be
considered. The team successfully collected air
muscle velocity and displacement data for a variety of
scenarios, future development into characterizing the
actuator’s response should be continued. An increased
continuity between projects needs to be emphasized;
therefore we constructed a universal and expandable
controls package that future teams can use with an
included instruction manual. This step forward will
help teams get off to a more productive start, instead
of trying to figure out how to turn on the system.
Some general recommendations for future teams in
this project track would be: using a microcontroller or
NI DAQ for compatibility reasons, reducing the slack
in the strings by improving mounting techniques,
using a less obtrusive clamp for attaching the air
muscle to the end fittings, not assuming linear change
for the theoretical force model, using a variable
regulator to improve system resolution, and using the
empirical response curves we generated to advance the
virtual simulation segment.
REFERENCES
[1] Kasper J., Lewis M., Hanzlik J., Cretekos E., Fike
J., Rappa N., McKann M., and Giang, E., 2008, "Air
Muscle Artificial Limb," Rochester Institute of
Technology., Rochester, New York.
[2] Tondu B., and Lopez, P., 2000, "Modeling and
Control of McKibben Artificial Muscle Robot
Actuators," IEEE Control Systems Magazine., 20(2),
pp. 15-38.
[3] LabVIEW Softmotion Tutorials.
ACKNOWLEDGMENTS
The team would like to thank those who helped us
throughout this project. Especially to our advisor, Dr.
Kathleen Lamkin-Kennard for her support. And also
to those that provided assistance through this time:
Edward Hanzlik, John Wellin, Dr. Mario Gomes, and
Sylvan Hemmingway.
Project P10029
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