Transcript Slide 1

Principles of
Engineering System Design
Dr T Asokan
[email protected]
Principles of
Engineering System Design
Bond Graph Modelling of
Dynamic systems
Dr T Asokan
[email protected]
Physical System Modelling
• Bond Graph Method
• The exchange of power between two parts of a
system has an invariant characteristic.
• The flow of power is represented by a Bond
• Effort and Flow are the two components of
power.
Classical approach for modeling of
physical system
Bond Graph Modeling
Physical System
Physical System
Engineering Model
Engineering Model
Differential Equations
Bond Graph
Block Diagrams
Software(Computer
Generated Differential Equations)
Simulation Language
Output
Output
Generalised Variables
Power variables:
Effort, denoted as e(t);
Flow, denoted as f(t)
Energy variables:
Momentum, denoted as p(t);
Displacement, denoted as q(t)
The following relations can be derived:
Power = e(t) * f(t)
p =
 e · dt
q =
 f · dt
Energy Flow
 The modeling of physical systems by means of bond graphs
operates on a graphical description of energy flows.
e
f
P=e·f
e: Effort
f: Flow
 The energy flows are represented as directed harpoons. The
two adjugate variables, which are responsible for the energy
flow, are annotated above (intensive: potential variable, “e”)
and below (extensive: flow variable, “f”) the harpoon.
 The hook of the harpoon always points to the left, and the
term “above” refers to the side with the hook.
October 2, 2008
Modeling: Bond Graph Basics
• effort/flow definitions in different engineering domains
Effort e
Flow f
Voltage [V]
Current [A]
Force [N]
Velocity [m/s]
Rotational
Torque [N*m]
Angular Velocity
[rad/sec]
Hydraulic
Pressure [N/m2]
Volumetric Flow
[m3/sec]
Chemical
Chemical Potential
[J/mole]
Molar Flow
[mole/sec]
Temperature
[K]
Entropy Flow
dS/dt [W/K]
Electrical
Translational
Thermodynamic
Modeling: Bond Graph Basic Elements
• I for elect. inductance, or mech. Mass
I
• C for elect. capacitance, or mech. compliance
C
• R for elect. resistance, or mech. viscous friction
R
• TF represents a transformer
e1
• GY represents a gyrator
e1
f1
f1
• SE represents an effort source.
SE
• SF represents a flow source.
SF
TF
e2
m
f2
GY
d
e2
f2
e2 = 1/m*e1
f1 = 1/m*f2
f2 = 1/d*e1
f1 = 1/d*e2
Modeling: Bond Graph Basic Elements
• Power Bonds Connect at Junctions.
• There are two types of junctions, 0 and 1.
5
1
4
0
3
11
1
2
13
12
Efforts are equal
Flows are equal
e1 = e2 = e3 = e4 = e5
f11 = f12 = f13
Flows sum to zero
Efforts sum to zero
f1+ f2 = f3 + f4 + f5
e11+ e12 = e13
Causal Bond Graphs
• Every bond defines two separate variables, the effort e and
the flow f.
• Consequently, we need two equations to compute values
for these two variables.
• It turns out that it is always possible to compute one of the
two variables at each side of the bond.
• A vertical bar symbolizes the side where the flow is being
computed.
e
f
•Mandatory Causality ( Sources, TF, GY, 0 and 1 Junctions)
•Desired Causality (C and I elements)
•Free Causality (R element)
“Causalization” of the Sources
The flow has to be
computed on the right
side.
Se
Sf
U
0
U0 = f(t)
i
u
The source computes the
effort.
I0 = f(t)
I0
The source computes the flow.
 The causality of the sources is fixed.
“Causalization” of the Passive
Elements
u
i
u
R
i
u=R·i
R
i=u/R
 The causality of resistors is free.
u
i
u
C
i
du/dt = i / C
I
di/dt = u / I
 The
causality of the storage elements is
determined by the desire to use integrators
instead of differentiators.
Integral Causality (desired Causality)
e
I
f
1
f   edt
I
f
F  ma
e
f
1
sI
e
e
C
f
1
sC
1
e   fdt
C
Integral causality is preferred when given a choice.
“Causalization” of the Junctions
e2
e1
f1
f2
0
f3
e3

e2 = e1
e3 = e1
f1 = f2 + f3
Junctions of type 0 have only one flow equation, and therefore,
they must have exactly one causality bar.
e2
e1
f1
f2
1
f3
e3

f2 = f1
f3 = f1
e1 = e2+ e3
Junctions of type 1 have only one effort equation, and therefore,
they must have exactly (n-1) causality bars.
Modelling Example Mechanical Systems
Mass, Spring and
Damper Syetms
x m
x 0
R
F
M
C
FR
Equation Governing the system
Mxm  Rx m  Kxm  F
F
Fm
Fk
Bond Graph model
Mass
I
Se
1
Velocity
Junction
0
Spring
1
Reference
Velocity=0 for
this case
Sf
1
Damper
C
R
System Equations
Final Bond Graph
Fm  FR  Fc  F
I
e1
Se
f1
em
fm
eR
1
ec fc
C
fR
R
1
ec   f c dt  K  x m dt  x m
C
Fc  Kx m
Simulation-Second order system
Modelling of underwater Robotic systems
Tx
MSe
Tbx
MSe
1
MR
Ixx+Iax I
1
wz*(Izz+Iaz)MGY
Iyy+Iay I
wy
1
MSe
Ty
MGY
wy*(Iyy+Iay)
MSe
Tbz
wz
1
I Izz+Iaz
MR
MSe
Tz
Fx
MSe
Linear velocity of the base
point w.r.t
Inertial frame
MTF
PV
1
Euler angle
MTF Transformation
matrix
1

Euler angles
MTF
TFMV
0
Vx
m+maxI
Body fixed
linear
velocity
1
MSe
Tby
1
Body fixed
angular
velocity
wx
MGY
wx*(Ixx+Iax)
MR
Angular velocity to
first link of the
manipulator
wz*(m+maz)
MGY
MTF
TFMV
m+mayI
MSe
Fby
Vy
1
MSe
Fy
Fbx
MSe
MR
1
MGY
wy*(m+may)
Vz
MGY
1
wx*(m+max)
MR
MSe
Fbz
I
MR
MSe
Fz
m+maz
Tip velocity
1
of the manipulator
Link 3
221
Pad
I
TF
TF1
Se
1
1
MTF
Joint velocity
TF
0
1
1
MTF
0
PV3
TFM3
MTF
MTF
PVM3
TFM3
Pad
Se
MR
TF2
TF
R
AD
L3
TF3
0
0
1
I
m3+ma3
MTF
Se
I
Se
Link 2
221
TF1
1
TF
1
Tip velocity
of Link2
1
MTF
0
TF
MTF
Joint velocity
0
1
1
TF2
Angular velocity
from previous link
TF
R
TF3
Pad
PV2
TFM2
MTF
MTF
PVM2
TFM2
Pad
0
Se
0
1
I
m2+ma2
AD
L2
MTF
MR
Se
Tip velocity
of link1
1
MTF
0
Iz1+Iaz1
I
Link1
1111as MR
ffa11
Wz1*(Izz1+Iaz1)
1
Wx1
angular velocity
of the manipulator
angular velocity
of the manipulator
Wy1*(Iyy1+Iay1)
MGY
MGY
1
Wy1
MR
1
MGY
1
Wx1*(Ixx1+Iax1)
I
Wz1
MR
Pad
I
Iy1+Iay1
MTF
PV1
TFM1
MTF
MTF
PVM1
TFM1
Pad
0
Se
0
MR
1
I
m1+ma1
Ix1+Iax1
I
Se
TF
TF1
Se
1
1
1
Joint velocity
TF
0
TF2
Angular velocity
from previous link
TF
R
TF3
MTF
Tx
Tbx
MSe
Ixx+Iax I
1
MSe
1 wx
MR
1
wz*(Izz+Iaz) MGY
Linear velocity of the base
point w.r.t
Inertial frame
Angular velocity to
first link of the
manipulator
Body fixed
angular
velocity
MGY
1
MTF
MTF
PV
TF
0
I
wy
1
MGY
wx*(Ixx+Iax)
wz
1
I Izz+Iaz
MR
MR
MSe
Ty
MSe
Tbz
MSe
Tby
1
Euler angle
MTF Transformation
matrix
MSe
MTF
1

Euler angles
1
MR
MGY
TF
m+may I
Vy
1
MGY
MR
MSe
MGY
wx*(m+max)
MSe
Fby
Fy
Tz
MSe
wz*(m+maz)
wy*(Iyy+Iay)
Iyy+Iay
Fbx
Vx
m+max I
Body fixed
linear
velocity
Fx
MSe
wy*(m+may)
Vz
1
MR
MSe
Fbz
I m+maz
MSe
Fz
Advantages and disadvantages of modelling and simulation
Advantages
• Virtual experiments (i.e. simulations) require less resources
• Some system states cannot be brought about in the real
system, or at least not in a non-destructive manner ( crash test,
deformations etc.)
• All aspects of virtual experiments are repeatable, something
that either cannot be guaranteed for the real system or would
involve considerable cost.
• Simulated models are generally fully monitorable. All output
variables and internal states are available.
• In some cases an experiment is ruled out for moral reasons, for
example experiments on humans in the field of medical
technology.
Disadvantages:
•Each virtual experiment requires a complete, validated and
verified modelling of the system.
•The accuracy with which details are reproduced and the
simulation speed of the models is limited by the power of the
computer used for the simulation.
SUMMARY
 Modelling and simulation plays a vital role in various stages
of the system design
 Data Modelling, Process Modelling and Behavior modelling
helps in the early stages to understand the system behavior and
simulate scenarios
 Dynamic system models help in understanding the dynamic
behavior of hardware systems and their performance in the
time domain and frequency domain.
Physical system based methods like bond graph method helps
in modelling and simulation of muti-domain engineering
systems.