Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14
Agenda:
- Background
- Modeling and simulation at UiA engng.
- Mathematical challenges
Mechatronic group at UiA
15 full time employed in teaching and labs.
Mechatronic profile at UiA characterized by:
• High power / Power Mechatronics
• Dynamic systems
• Off Shore applications
Mechatronic profile at UiA, programmes:
• 3 years B.Sc., since 1988
• 2 years M.Sc., since 2008
• 3 years Ph.D., since 2010
- Conclusions
DESIRED MECHATRONIC PROFILE
Campus Kristiansand
MODELING
VIRTUAL PROTOTYPING
Campus Grimstad
Kristiansand
Grimstad
EXPERIMENTAL
WORK
MEHCATRONIC DESIGN
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14
Modeling and Simulation at the Engineering MSc educations at UiA
Mechatronics and Renewable Energy
Dedicated course (10SP)
Used in subsequent courses on mechanics, hydraulics, electrical drives,
control, instrumentation, industrial information technology, product
development.
Used in multidisciplinar project works (across individual courses)
Used extensively in graduate projects
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14
Simulation
Mainly time domain simulation and numerical methods
Why time domain simulation ?
- Investigate dynamic characteristics
- Avoid or minimize physical testing
- Gain insight into non-linear behavior
- Gain insight into parameters that are difficult to measure physically
- Extensively used in industry to predict and verify design
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14
Simulation
Mainly time domain simulation and numerical methods
Why time domain simulation ?
- Investigate dynamic characteristics
-University
Avoid or minimize
testinganalysis and optimization - competencies
of Agder -physical
Model based
Simulation
- Gain insight into non-linear behavior
- Gain insight into parameters that are difficult to
measure physically
- Extensively used in industry to predict and
verify design
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14
Simulation
Mainly time domain simulation and numerical methods
Why numerical methods ?
- Practical problems typically outside the scope of analytical solutions
- Allows for the handling of large scale problems
- Allows for design optimization
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14
MATHEMATICAL CHALLENGES:
- WHITE BOX MODELING, DIFFERENTIAL EQUATION OF MOTION
- GRAY BOX MODELING, IMPACT WITH WALL
- NUMERICAL SOLUTION, TIME INTEGRATION
Simple system with no analytical solution
Simple system with no analytical solution
g
L
    sin 
    sin 
L
L

g
L

m
m
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14
FURTHER MATHEMATICAL CHALLENGES:
- TRIGONOMETRY.
- BLACK BOX MODELING, TIRE MODEL, BUMP IN ROAD.
Simple system with no analytical solution
Simple system with no analytical solution
20
A
B
y
hs
x
y( t  0 )  1.2 m
y
L
x0
x


h
h( x )   s
2


0
x  x0

L 
 2  
  1  sin 
  x  x0     x0  x  x0  L
4 
 L 

0
x  x0  L
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14
MATHEMATICAL CHALLENGE:
FORMULATE DESIGN PROBLEM (INVERSE ANALYSIS)
Michael R. Hansen, MatRIC meeting, Grimstad 27/5-14
IN CONCLUSION
MAIN MATHEMATICAL CHALLENGES:
- WHITE BOX MODELING, PURELY PHYSICAL (Newtons 2nd law, Ohms law).
- GRAY BOX MODELING, PARTLY PHYSICAL - PARTLY EMPIRICAL (Parameter identification,
friction, impact, damping).
- BLACK BOX MODELING, PURELY EMPIRICAL RELATIONSHIPS (Forcing mathematical
expressions on observations, measurements, or assumed dependencies).
- SETTING UP NUMERICAL SOLUTIONS (Time integration, nonlinear equations,
optimization).
- TRIGONOMETRY.