Mechatronics at the
University of Calgary:
Concepts and Applications
Jeff Pieper
Outline
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Mechatronics
Past and Present Research Results
Undergraduate Program
Directions for the Future
Summary
What is Mechatronics?
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Synergistic combination of mechanics,
electronics, microprocessors and control
engineering
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Like concurrent engineering
Does not take advantage of inherent uniqueness
available
Control of complex electro-mechanical
systems
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Rethinking of machine component design by use
of mechanics, electronics and computation
Allows more reconfigurablility
What is Mechatronics
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Design example: timing belt in
automobile
Timing belt mechanically synchronizes
and supervises operation
Mechatronics: replace timing belt with
software
Allows reconfigurability online
What is Mechatronics
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Second example: Active suspension
Design of suspension to achieve
different characteristics under different
operating environments
Demonstrates fundamental trade-offs
What is Mechatronics
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Low tech, low cost, low performance: pure
mechanical elements: spring shock absorber
 Can use dynamic systems to find coefficients via
time or frequency domain
mid tech, cost, performance: electronics: op amps,
RLC circuits, hydraulic actuators
 Typically achieve two operating regimes, e.g.
highway vs off-road
High tech, cost , performance: microprocessor-based
online adjustment of parameters
 Infinitely adjustable performance
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Research Projects
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Discrete Sliding Mode Control with Applications
Helicopter Flight Control
OHS Aircraft Flight Control
Magnetic Bearings in Papermaking Systems
Robust Control for Marginally stable systems
Process Control and System ID
Controller Architecture
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Theme of research
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Control of
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Uncertain
Nonlinear
Time-varying
Industrially relevant
Electro-mechanical systems
This is control applications side of
mechatronics
Involves sensor, actuator, controller design
What is control?
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Nominal performance
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Servo tracking
Disturbance rejection
Low sensitivity
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Minimal effects of unknown aspects
Non-time-varying
Feedback Control
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Discrete Time Sliding Mode
Control
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Comprehensive evaluation of theoretical
methodology
Optimization, maximum robustness
Applications:
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Web tension system
Gantry crane
Web Tension System
Gantry Crane
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Helicopter Flight Control
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Experimental Model Validation
Model-following control design
Experimental Flight Control
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Multivariable
Start-up and safety
Helicopter Flight Control
Helicopter Flight Control
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Model-following vs. stability
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Conflicting Multi-objective
Controller Optimization
Order reduction
System validation
Helicopter Flight Control
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OHS Aircraft Flight Control
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Outboard Horizontal Stabilizer
Non-intuitive to fly
Developed sensors and actuators
Model identification and validation
Gain-scheduled adaptive control
Reconfigurable controller based upon
feedback available
OHS Aircraft
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15
20 m/s
25
4
20
Angle of Attack (deg)
Airspeed (m/s)
15
2
0
-2
-4
10
5
0
-5
-10
-15
-20
-25
0
1
2
3
4
0
1
2
3
4
0
1
2
3
4
0
1
2
3
4
30
100
75
Pitch Rate (deg/s)
20
Pitch (deg)
10
0
-10
-20
50
25
0
-25
-50
-75
-30
-100
0
1
2
3
4
2.0
10
8
Elevator Deflection (deg)
1.5
Altitude (m)
1.0
0.5
0.0
-0.5
-1.0
-1.5
-2.0
6
4
2
0
-2
-4
-6
-8
-10
0
1
2
Time (s)
3
4
Time (s)
Magnetic Bearings in
Papermaking Systems
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System identification for magnetic
bearings
Nonlinear, unstable system
Closed loop modeling
Control Design using Sliding Mode
methods and state estimators
Servo-Control of shaft position
Magnetic Bearings
20
50
Frequency (Hz)
100
200
500
1000
2500
20
50
2
1000
2500
1.5
-1
-50
0
0
50
50
100
150
100
1
Yhl
U hl
0
-50
)ged( e sahP
)ged( e sahP
1
0.5
150
200
200
250
250
0
-2
-3
-0.5
5
20
-60
)Bd( edu tingaM
1
U hr
0
-1
-2
50
15
Frequency (Hz)
100
200
500
20
1000
25
0
2500
20
-60
-50
-50
-40
-40
-30
-30
)Bd( edu tingaM
2
10
-20
-10
10
Frequency (Hz)
100
200
500
15
1000
20
25
20
25
2500
1
0.5
-10
0
10
10
0
-0.5
20
Yhl/U hl
0
5
-20
0
20
50
Yhr
0
-3
Frequency (Hz)
100
200
500
5
10
15
Time (mS)
Yhr/U hl
20
25
-1
0
5
10
15
Time (mS)
Magnetic Bearings in
Papermaking Systems
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Papermaking system modeling
Use of mag bearings for tension control
actuation and model development
Control Design and implementation
issues
Compare performance with standard
roller torque control
Papermaking Tension Control
The H-infinity norm of different order apprx system
The H-infinity norm of transfer function of PID controller by changing velocity
1.4
2.6
2nd order approx
4th order approx
6th order approx
10th order approx
H-infinith norm of transfer function
1.3
2.4
The H-infinity norm of transfer function
1.35
1.25
1.2
1.15
1.1
1.05
1
2
1.8
1.6
1.4
1.2
1
0.95
0.9
2.2
0
0.05
0.1
0.15 0.2 0.25 0.3 0.35 0.4
Cross-sectional Area of web material
0.45
0.5
0.8
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
2
Cross-sectional Area of web material(in. )
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Robust Control
via Q-parameterization
x
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Ball and beam application
Stability margin optimization: Nevanlinna-Pick
interpolation
Experimental Results
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Large lag
Non-minimum phase
behaviour
Friction, hard limits
Robust Stability Margin
Delay
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
Nominal
-0.27
-0.26
-0.19
-0.07
0.06
0.17
0.26
0.34
0.39
0.44
0.48
0.51
0.54
0.56
0.58
0.60
Optimal
-0.30
-0.28
-0.22
-0.11
0.01
0.10
0.18
0.24
0.29
0.33
0.37
0.40
0.42
0.44
0.46
0.47
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Process Control and System ID:
Quadruple-tank Process Diagram
Out2
Out1
G11
G12
PUMP1
Out2
Out1
Tank1
L1
G21
Tank2
L2
G22
PUMP2
Tank3
L3
Tank4
L4
System ID: Model Fitting
Tank4 process model
with input u1
Tank2 process model
with input u1
Control Techniques
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Classic PI control
Internal Model Control (IMC)
Model Predictive Control (MPC)
Linear Quadratic Regulator (LQR)
Optimal Control
MPC Control Results
Different set points changes to test MPC
controller performance
Tank2 response
Tank4 response
Performance Comparison
Controllers
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PI
IMC
MPC
LQR
MP(%)
4
20
5
32
ts (sec)
31
99
50
210
ss e(%)
1.5
0
0
0
||e||2
2.7
0.8
0.45
0.3
||e||
0.2
0.08
0.05
0.05
trc(sec)
34
102
47
76
Parameters
Controller Architecture
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Given conflicting and redundant
information
Design controller with best practical
behaviour
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Good nominal performance
Robust stability
Implementable
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Undergraduate Program:
Mechatronics Lab with Applications
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Developed lab environment for teaching and research
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Two courses: - linear systems, - prototyping
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Hands-on work in:
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modeling
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system identification
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Sampled-data systems
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Optical encoding
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State estimation
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Control design
Mechatronics Lab with Applications
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Multivariable fluid flow control system
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Two-input-two-outputs
Variable dynamics
Model Predictive Control
Chemical Process Emulation
Fluid Flow Control
Quanser Product
Mechatronics Lab with Applications
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Ball and Beam system
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Hierarchical control system
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Motor position servo
Ball position
Solve via Q-parameterization
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Robust stability and optimal nominal
performance
Ball and Beam System
Quanser Product
Mechatronics Lab with Applications
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Heat Flow Apparatus
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Unique design
Varying deadtime for challenging control
Demonstrate industrial control schemes
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PID controllers
Deadtime compensators
Heat Flow Apparatus
Quanser product
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Directions for the Future
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Robust Performance
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Multiobjective Control Design
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Systems that meet conflicting, and disparate
objectives
Performance evaluation for soft measures
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robust stability and nominal performance
simultaneously guaranteed
Fuzzy systems
Bottom line: Mechatronics
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Summary
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Control applications in electromechanical systems
Emphasis on usability
Complex problems from simple systems
Undergraduate program: hands-on
learning and dealing with systems form
user to end-effector