model-based real-time hybrid simulation for large-scale experimental evaluation
DESCRIPTION
Model-based Real-Time Hybrid Simulation for Large-Scale Experimental Evaluation. Brian M. Phillips University of Illinois. B. F. Spencer, Jr. University of Illinois. Yunbyeong Chae Lehigh University. Tony A. Friedman Purdue University. Karim Kazemibidokhti Lehigh University. - PowerPoint PPT PresentationTRANSCRIPT
Model-based Real-Time Hybrid Simulation for Large-Scale Experimental Evaluation
Brian M. PhillipsUniversity of Illinois
B. F. Spencer, Jr.University of Illinois
Yunbyeong ChaeLehigh University
Karim KazemibidokhtiLehigh University
Shirley J. DykePurdue University
Tony A. FriedmanPurdue University
James M. RiclesLehigh University
Quake Summit 2012Boston, Massachusetts
June, 2012
INTRODUCTION
2
Large-Scale RTHS Project Performance-based design and real-time, large-scale
testing to enable implementation of advanced damping systems
Joint project between Illinois, Purdue, Lehigh, UConn, and CCNY
3
Hybrid Simulation Loop
Servo-hydraulic system introduces dynamics into the hybrid simulation loop
Actuator dynamics are coupled to the specimen through natural velocity feedback
When multiple actuators are connected to the same specimen, the actuator dynamics become coupled 4
NumericalSubstructure
u ExperimentalSubstructure
Sensorsffmeas
xLoadingSystem
Servo-Hydraulic System
gx
SERVO-HYDRAULIC SYSTEM MODEL
5
MIMO System Model
6
+
− −
Servo-Hydraulic System Gxu(s)
Natural Velocity Feedback
Actuator Specimen
sGa sGxf
As
sGs
Servo-Controllerand Servo-Valve
+
3
2
1
uuu
u
3
2
1
xxx
x
3
2
1
fff
f
s
s
s
s
000000
kk
ksG
AA
AA
000000
a
a
a
a
a
a
a
00
00
00
psk
psk
psk
sG
Multi-Actuator Setup
3
2
1
3
2
1
333231
232221
131211
3
2
1
333231
232221
131211
3
2
1
333231
232221
131211
fff
xxx
kkkkkkkkk
xxx
ccccccccc
xxx
mmmmmmmmm
Equations of motion:
7
1x
2x
3x Actuator 3
Actuator 1
Actuator 2
3f
2f
1fServo-Controller 1
Servo-Controller 2
Servo-Controller 3
Computer Interface
MIMO System Model
AA
AA
000000
a
a
a
a
a
a
a
00
00
00
psk
psk
psk
sG
s
s
s
s
000000
kk
ksG
1
33332
3332322
3231312
31
23232
2322222
2221212
21
13132
1312122
1211112
11
kscsmkscsmkscsmkscsmkscsmkscsmkscsmkscsmkscsm
sG xf
Component models:
Servo-hydraulic system model:
sGsGAssG
sGsGsGsG
xfas
xfasxu
I
+
− −
Servo-Hydraulic System Gxu(s)
Natural Velocity Feedback
Actuator Specimen
sGa sGxf
As
u f x sGs
Servo-Controllerand Servo-Valve
+
8
MODEL-BASED ACTUATOR CONTROL
9
Regulator Redesign
10
uzz BA zx C
xre
uzz BA
rzx C
Servo-hydraulic system transfer function in state space:
Tracking error:
Ideal system with perfect tracking:
zzz ~uuu ~
xxx ~
uzz ~~~ BA
ezx ~~ C
Deviation system:
Model-Based ControlFeedforward Feedback Links
11
FBFF~ uuuuu
Total control law is a combination of feedforward and feedback:
GFF(s)
LQG Gxu(s)e uFB
uFF
u
Feedforward Controller
Feedback Controller Servo-Hydraulic Dynamics
+- +
+r x
LARGE-SCALEEXPERIMENTAL STUDY
12
Prototype Structure
13
Actuator 3
Actuator 1
Actuator 2
Experimental Substructure
0 10 200
0.5
1
1.5
0 10 200
0.02
0.04
0 10 200
0.02
0.04
TF DataModel
0 10 200
0.02
0.04
Mag
nitu
de
0 10 200
0.5
1
1.5
0 10 200
0.02
0.04
0 10 200
0.02
0.04
0 10 200
0.02
0.04
Frequency (Hz)0 10 20
0
0.5
1
1.5
MIMO Transfer FunctionMagnitude
14
Input 1 Input 2 Input 3
Output 1
Output 2
Output 3
0 10 20-150
-100
-50
0
0 10 20-200
0
200
0 10 20-200
0
200
TF DataModel
0 10 20-200
0
200
Pha
se (
)
0 10 20-200
-100
0
100
0 10 20-200
0
200
0 10 20-200
0
200
0 10 20-200
0
200
Frequency (Hz)0 10 20
-150
-100
-50
0
MIMO Transfer FunctionPhase
15
Input 1 Input 2 Input 3
Output 1
Output 2
Output 3
5 Hz BLWN Tracking
16
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
-20
2
Dis
p 1
(mm
)
desiredNo CompFF + FB w / Coupling
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
-2
0
2
Dis
p 2
(mm
)
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
-20
2
Dis
p 3
(mm
)
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
0
1
23
Cur
rent
(A
)
Time (sec)
RMS Error Norm
No Comp: 44.8%FF + FB: 3.75 %
No Comp: 47.8%FF + FB: 4.43 %
No Comp: 50.8%FF + FB: 4.39 %
15 Hz BLWN Tracking
17
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
-1
0
1
Dis
p 1
(mm
)
desiredNo CompFF + FB w / Coupling
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
-1
0
1
Dis
p 2
(mm
)
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
-1
0
1
Dis
p 3
(mm
)
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
0
1
23
Cur
rent
(A
)
Time (sec)
No Comp: 97.8%FF + FB: 10.7 %
No Comp: 96.6%FF + FB: 13.5 %
No Comp: 98.1%FF + FB: 11.5 %
RMS Error Norm
Prototype Structure
18
Actuator 3
Actuator 1
Actuator 2
Mode fn (Hz) x
1 1.27 3.00%
2 4.04 6.00%
3 8.28 6.00%
Total Structure Experimental Substructure
Ground acceleration 0.12x NS component
1994 Northridge earthquake Numerical integration
CDM at 1024 Hz Actuator control
FF + FB control w/ coupling Structural control
Clipped-optimal control algorithm (Dyke et al., 1996)
RTHS Parameters
19
0 10 20 30 40 50-0.1
-0.050
0.050.1
Time (sec)
Acc
el (
g)
Semi-Active RTHS Results0.12x Northridge
20
0 2 4 6 8 10 12 14 16 18 20-5
0
5
Dis
p 1
(mm
) 0 2 4 6 8 10 12 14 16 18 20
-100
10
Dis
p 2
(mm
) 0 2 4 6 8 10 12 14 16 18 20
-20
0
20
Dis
p 3
(mm
)
SimFF + FB w / Coupling
0 2 4 6 8 10 12 14 16 18 200123
Cur
rent
(A
)
0 2 4 6 8 10 12 14 16 18 20-0.1
0
0.1
Grn
d A
cc (
g)
Time (sec)
-5 0 5-100-50
050
100
Displacement (mm)
Forc
e (k
N)
-50 0 50-100-50
050
Velocity (mm/s)
CONCLUSIONS
21
Conclusions The source of actuator dynamics including actuator
coupling has been demonstrated and modeled A framework for model-based actuator control has been
developed addressing Actuator dynamics Control-structure interaction
Model-based control has proven successful for RTHS Robust to changes in specimen conditions Robust to nonlinearities Naturally can be used for MIMO systems
22
Thank you for your attention
23
The authors would like to acknowledge the support of the National Science Foundation under award CMMI-1011534.