A new servo controller
for a Materials Testing
Machine - MTM
Final Presentation a
David Schwartz & Uri goldfeld
Supervisor : Daniel Alkalay
General System Description
The MTM system we work on is a
mechanical system that allows us to
test the physical properties of materials
and structures.
Testing is done by applying static or
dynamic loads, using an hydraulic
actuator in closed-loop servo control.
Feedback for closed loop control uses
displacement OR Strain sensors.
The MTM system enables us to
determine tensile/compressive
strength, fatigue resistance, crack
growth resistance ect.
Strength:
The machine applies force on a specimen in order to
find out stress Vs. strain characteristics
Fatigue:
This test is vital for materials who are under a
cyclic force for example: plane wings,bridge…
Here the machine applies a periodic (Sin,
Square,saw tooth) waveform and checks the
behavior under different frequencies and
amplitudes.
Our machine:
The Original System
General abstract
The
Electrical
Control
system
Servo Valve
+
Hydraulics
Function
Generator
Intelocks
Sensors
The
Hydraulic
Controller
control
Itself
Main Project Goals
The global purpose is to develop a modern computer based
mechanical testing system, using current hardware and
software tools.
Part A:
Servo
+
hydraulics
Part B:
Old
Software
control
controller
system
FPGA
LabView
Project Goals of Part A:
Implementing a new control system for the
MTM machine Located at the Material
Mechanics Laboratory.
• Learning LabVIEW
• Learning the required control tools
• Performing system identification
• Implement a simulation environment
• Simulate the whole system using our controller
• Keeping the environment General so it’ll fit
other possible systems
The control loop
Command
+
-
Force = 1
Displacement=2
PID controller
1
2
MTM
Load cell
LVDT
The machine is controlled in a closed loop.
The control loop is modeled as an SISO LTI system.
What is PID
Set point = Command
Process variable = The Sensors output
What characteristics should we check
Stage 1: System identification
•
•
•
•
•
•
•
Learning LabView deeply
Learning MatLab System identification tool
Finding the 3dB point of the hole system
Finding Overshoot% and Tsettling and Trise_time
Finding dominant poles (W n and z)
Working with function generator while controlling
it using LabView
Finding Bode plot Gain + Phase of the system
The measurement system
MTM
I/O card 6036
Agilent Waveform generator
RS232
MatLab:
pc
LabView:
The Measuring Environment
We want to measure the TF of the whole system meaning, we
give the command to the -> controller who calculates the
control signal
->To servo ->Back throw sensors to the controller.
We sniff the sensors output and calculate the TF by it
• The original FULL system was running while our LabVIEW
software provided the input and sampled the sensors.
• The sampled sensor was the LVDT sensor
• measurement influence: we used E-6036 card to sample the
LVDT. If there was any influence on the results they are
probably insignificant and we can handle them by autotuning.
TF measurements Using LABVIEW
Send waveform properties
To signal generator via
RS232
Write to file for further
Post processing with
matlab
Read generator’s output
signal and MTM’s output
signal via sampling card
Do preliminary
calculations (such as
gain and phase)
Step response measurements
Step response to 1Hz rectangular wave, amplitude 1Volt
Sampling rate is 1KHz:
Trise_time=106ms
O.S%= 0.5%
Tsettling= 140ms
Finding Bode plot Gain + Phase of the system
This was done using a VI that generated Freq. steps
between 0.01Hz to 60Hz,sampeling the Gain and
Phase for each Freq.
Gain
Bode Diagram
20
0
System: sys
Frequency (rad/sec): 1.11
Magnitude (dB): 0.637
Magnitude (dB)
-20
System: sys
Frequency (rad/sec): 86.1
Magnitude (dB): -10.2
-40
-60
-80
-100
0
Phase (deg)
-45
Phase
-90
System: sys
Frequency (rad/sec): 86.6
Phase (deg): -90
-135
-180
0
10
1
10
2
10
Frequency (rad/sec)
3
10
4
10
MTM System’s TF
• The approximated Transfer function:
8097
-------------------s^2 + 303.5 s + 7518
The poles are real
-276.2874
-27.2106
The system is over damped:
Xi=1.75>1
3db point : 4.344 Hz
Stage 2: Isolating the controller
• Learning current system properties from
•
•
•
•
available engineering documentations.
Abstracting the control system
Replace the servo valve with equivalent
resistance , repeating the system identification
process on the controller without the actuator.
Calculating the transfer function of the controller
The measuring system:
– We use a new M-series hardware for measuring and
activating the controller
– Since the valve is disconnected the sensors will give
the controller same value all the time thus what we
will measure on the resistors will be the response of
the controller as pure as possible while the whole
system works
The measurement system (with internal signal
generator)
I/O M series card
MTM controller
pc
LabView:
•Gain and
phase
calculations
•Signal
generation
The Measuring Environment
Generate signal in software -> input to the controller ->controller gives
command to servo -> We sample the given command on the resistors
• The controller is not connected to the valve but to the resistors
• We do not sample any sensor but the DC_ERROR signal coming out
of the controller
• We expect no meaningful influence on the results caused by our
measurement
Phase(deg)
Magnitude(dB)
Bode Plot of the MTM Controller
MTM controller TF
Transfer function :
2.052e008
----------------------------s^2 + 1.666e004 s + 7.529e007
Xi=0.96
MTM_Controller_3dB point = 921Hz
The Controller’s 3dB point is 212 times then
entire system 3db (4.344 Hz)
Conclusion:
Mainly a P controller with Kc~=2.72
The simulation program
Labview VIs:
NI DAQmx
read
•Limit +interlock
check
fail
Stop
program
o.k
PI
Control signal
Signal generator
H(s)
NI DAQmx
write
System Overview
sensors
Initial interlock
check
(*)
Limits
(**)
OK
NOT OK
stop
Function
Generation
specification
+
Set Point
Stop
Signal
generation
FA
IL
(*)
(**)
Controller
Limits &
Interlock
check
OK
Dither
Sampling
card
Sensors
AMP
Servo
Valve
Stage 3: Building a simulation
• A simulation in LabVIEW for the system was
•
built using the acquired transfer function to
simulate The servo valve and acquired PID
parameters to simulate the controller
Labview auto tuning vi’s were used to find better
PID parameters.Manual tuning is also possible.
Simulation results
Simulating Square Input to the machine
Simulating Sin input to the machine
Simulating Sin input to the machine
Simulating Square Input to the machine
Difficulties
• Main difficulty is that in order to check our
•
simulation system we need a special Amplifier
which we currently don’t have.
Attempts were made to use the old controller’s
Amplifier but it can’t be done.
To continue we must build or buy the amplifier
that will enable us to check our software directly
on the servo valve
Summary
These are the results we got for optimal gains:
• No overshot (0%)
• Rise time of 15 msec
• Settling time of 30 msec (to a sleeve of +- 5%)
If we look at the full system identification we see that the
original system had a WORSE response :
• No overshot (0%)
• Rise time of 100 msec
• Settling time of 140 msec (to a sleeve of +- 5%)
Meaning that in simulation the controller we have now is
the much better than the original controller, Thus we
should expect the hardware implementation to bring
better results then the old controller
Future Work
Dates
assignments
On going
(Long)
Learning the LabVIEW FPGA module
Two-Three
weeks
Defining the architecture of the combined
system I.E what will be on FPGA and what
on the LabVIEW_RT
One-Two
weeks
Emulate our system before using the FPGA
Two-Three
weeks
Use the whole system as one synchronized
unit and checking it as the new full controller
One-Two
week
Project book and Final presentation