Transcript Quake Summit 2011 Buffalo, NY

Real Time Hybrid Simulation
for Validation of
Advanced Damping Systems on
Large-Scale Applications
(NEESR Project 648)
Anthony Friedman
Quake Summit 2012 - Boston, MA
2
NEESR Team
Shirley Dyke
Tony Friedman
Ali Ozdagli
James Ricles
Rich Christenson
Ryan Ahn
Nestor Castaneda
Anil Agrawal
Bill Spencer
Richard Sause
Yunbyeong Chae
Brian Phillips
Zhaoshuo Jiang
Youngjin Cha
Jianqui Zhang
Baiping Dong
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Performance–
Based Design
MR Damper
Control
Control Performance
Validation
Real-Time
Hybrid
Simulation
Actuator
Motion
Control
4
Performance–
Based Design
MR Damper
Control
Control Performance
Validation
Real-Time
Hybrid
Simulation
Actuator
Motion
Control
5
Performance-Based Design
• A Simplified Design Procedure (SDP) (Chae 2011) is used to
perform an integrated design of the perimeter moment
resisting frames (MRFs), the damped braced frames (DBFs),
gravity frames, and dampers to achieve performance
objectives for the building.
North
West
East
South
Tributary seismic area
South
North
PG3
PG2
PG1
MRF
DBF
Lean-on
column
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Performance-Based Design
Diaphragm
W10x17
3rd floor
W12x40
HSS8x6X3/8
RBS
W14x38
RBS
RBS Beam-columnPG3
connection
2nd floor
W12x40
HSS8x6X3/8
W18x46
1st floor
W18x46
MRF
HSS8x6X3/8
Ground floor
Basement
Damper Frame
MRF
MRF
DBF
Elevation view of test frame
W8x76
W8x76
W12x40
CBF
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Performance–
Based Design
MR Damper
Control
Control Performance
Validation
Real-Time
Hybrid
Simulation
Actuator
Motion
Control
8
MR Damper Control
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•
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Manufactured by Lord Corporation
200 kN force capacity
1.47 m (58 inches) in length
Stroke of 584 mm (23 inches)
Controlled with an Advanced Motion Controls PWM
amplifier and an 80 V DC power supply
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MR Damper Control
• MR fluid consists of micron-sized particles
suspended in a carrier oil. Application of a
magnetic field induces particle chains to form.
Force (kN)
200
100
0
-100
-200
0
0.5
1
1.5
2
2.5
Time (sec)
0.5 A
1A
1.5 A
200
200
100
100
Force (kN)
Force (kN)
0A
0
-100
-200
-30
2A
2.5 A
0
-100
-200
-20
-10
0
10
Displacement (mm)
20
30
-100
0
100
Velocity (mm/sec)
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MR Damper Control
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Control Design
• Advanced damping systems offer flexibility in
achieving a myriad of goals in performancebased design
• Semi-active control offers the benefits of active
and passive control
• Low power level requirements
• Dissipative
• Stability
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Control Approaches
• Consider large-scale device dynamics
• Over- and back-driving the damper (ODCOC)
• Practical design for easy implementation
• Device-mounted simple passive controller (SPC)
• Optimal Control
• Decentralized Output Feedback Polynomial controller
(DOFPC)
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ODCOC
MR Damper Rise Time
200
180
200
160
140
Force (kN)
Force (kN)
150
100
50
0
-0.5
0
0.5
1
Displacement (mm)
1.5
1A
2.5 A
3A
4A
5A
6A
7A
28 A
Force Rise Time at constant 50 mm/sec
120
100
80
60
40
20
0
5.5
0A
-1A
-2.5A
-3A
-4A
-5A
-6A
-7.5A
6
6.5
Time (sec)
7
7.5
Force Decay Time at constant 50 mm/sec
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SPC
V
V3
V3
V1
V2
V2
X
X3
X2
X1
X1
X2
X3
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DOFPC
• Uses an optimization routine to select
polynomial coefficients
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Performance–
Based Design
MR Damper
Control
Control Performance
Validation
Real-Time
Hybrid
Simulation
Actuator
Motion
Control
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Coupled Actuator Systems
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Coupled Actuator Systems
• Servo-hydraulic systems introduces dynamics into the RTHS loop
• Actuator dynamics are coupled to the specimen through the
natural velocity feedback
• When multiple actuators are connected to the same specimen,
the actuator dynamics become coupled
 u1 
 
u  u 2 
u 
 3
 f1

f   f2
f
 3
Servo-Hydraulic System Gxu(s)
+
−
Gs s 
Servo-Controller
and Servo-Valve
+
−





Ga s 
Gxf s 
Actuator
Specimen
As
Natural Velocity Feedback
 x1 
 
x   x2 
x 
 3
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Model-Based Multi- Actuator
Control
• Model-based multi-actuator control is designed to eliminate
the modeled dynamics of the servo-hydraulic system (Phillips
2012)
Total control law is a combination of feedforward and feedback:
GFF(s)
uFF
Feedforward Controller
r
+
+
e
-
LQG
uFB
Feedback Controller
+
u
Gxu(s)
Servo-Hydraulic
Dynamics
x
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Performance–
Based Design
MR Damper
Control
Control Performance
Validation
Real-Time
Hybrid
Simulation
Actuator
Motion
Control
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Real-Time Hybrid Simulation
Target PC
Substructure
Sensor
Measurements
Analytical
Substructure
MRD
Command
Experiment
Experimental
Substructure
Actuator
Sensor
Signals
DAQ
Actuator
Command
Actuator
Sensor
Signals
Sensors
Actuator
Valve
Command
Servo-hydraulic
Controller
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Frame Identification
• Conducted quasi-static testing to determine
the inter-story stiffness values (Ahn 2012)
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MR Damper Identification
• Constant/Step current testing
• Insert new photo
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Real-Time Hybrid Simulation
• Perform RTHS with two structures
• 3-Story Prototype Structure
• 9-Story Benchmark Structure
• Multiple damper deployment schemes are
considered
• Examine global response characteristics under
various seismic inputs
• Examine controller robustness in various
scenarios
• Examine RTHS repeatability
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Real-Time Hybrid Simulation
Gravity
frames
xg
Structure with
MR dampers
W3
PG3
W2
PG2
W1
PG1
Analytical substructure
Gravity System + MRF
Experimental substructure
DBF + MR damper
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Performance–
Based Design
MR Damper
Control
Control Performance
Validation
Real-Time
Hybrid
Simulation
Actuator
Motion
Control
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Control Performance Validation
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Control Performance Validation
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Control Performance Validation
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Control Performance Validation
Floor 9 Disp - ODCOC
0.04
SIM
RTHS
0.03
Displacement (m)
0.02
0.01
0
-0.01
-0.02
-0.03
-0.04
0
10
20
30
40
50
60
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Control Performance Validation
Floor 9 Vel - ODCOC
0.15
SIM
RTHS
0.1
Velocity (m/sec)
0.05
0
-0.05
-0.1
-0.15
-0.2
0
10
20
30
40
50
60
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Control Performance Validation
Floor 9 Acc - ODCOC
0.6
SIM
RTHS
0.4
Acceleration (m/sec 2)
0.2
0
-0.2
-0.4
-0.6
-0.8
0
10
20
30
40
50
60
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Control Performance Validation
ELC
Disp.
Drift
Acc.
Force (kN)
Reduction Reduction Reduction
PON
26.2%
58.3%
12.1%
145
COC
23.7%
21.8%
17.1%
99
ODCOC
22.9%
28.7%
28.0%
93
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Control Performance Validation
ELC
Disp.
Drift
Acc.
Force (kN)
Reduction Reduction Reduction
PON
26.2%
58.3%
12.1%
145
COC
23.7%
21.8%
17.1%
99
ODCOC
22.9%
28.7%
28.0%
93
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Control Performance Validation
ELC
Disp.
Drift
Acc.
Force (kN)
Reduction Reduction Reduction
PON
26.2%
58.3%
12.1%
145
COC
23.7%
21.8%
17.1%
99
ODCOC
22.9%
28.7%
28.0%
93
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Control Performance Validation
• SIM and RTHS results compare well
• Semi-active controllers are superior in terms
of acceleration response reduction (~15%
improvement)
• Semi-active controller were able to achieve
superior response reductions while also using
less force
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Performance–
Based Design
Actuator
Motion
Control
Control Performance
Validation
Real-Time
Hybrid
Simulation
MR Damper
Control
38
Accomplishments
• Developed and applied SDP for an integrated design
• Developed and successfully employed a real-time
actuator tracking controller on multiple actuators
attached to a large-scale steel frame
• Implemented several newly developed semi-active
control methods for large-scale MR dampers
• Successfully performed large-scale RTHS
• 3-Story Prototype Structure
• 9-Story Benchmark Structure
• Considered multiple damper deployment schemes
• Validated controller performance and demonstrated
improved response reductions using MR Dampers and SA
control for several seismic inputs
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Educational Activities
AAAS Exhibition Booth
EPICS Course
EERI Competition
REU Korea Project
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Dissertations
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Chae, Y., (2011) "Seismic Hazard Mitigation of Building Structures using
Magneto-rheological Dampers," Ph.D. Dissertation, Lehigh University
Jiang, Z., (2011) “ Increasing Resilience in Civil Structures Using Smart Damping
Technology” Ph.D. Dissertation, University of Connecticut
Phillips, B.. (2012) “Model-based Feedforward-Feedback Control for Real-Time
Hybrid Simulation of Large-Scale Structures” Ph.D. Dissertation, University of
Illinois – Urbana/Champaign
Castaneda, N., (2012) “Development / Validation of a Real-time Computational
Framework for Hybrid Simulation of Dynamically-excited Steel Frame
Structures” Ph.D. Diss., Purdue University
Zhang, J., (2012) “A Novel MR Damper-based Semi-Active Control System for
Seismic Hazard Mitigation of Structures” Ph.D. Dissertation, City University of
New York
Friedman, A., (2012) “Development and Experimental Validation of Control
Strategies for Advanced Damping Systems using Real-Time Hybrid Simulation”
Ph.D. Dissertation, Purdue University
Dong, B., (2012) TBD, Ph.D. Dissertation, Lehigh University
Ahn, R., (2012) TBD M.S. Thesis, Lehigh University
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Data Sets – Project 648
• MR Damper Characterization Tests
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Phillips, B., et al., MR Damper Characterization - UIUC - Damper 3
www.nees.org DOI – TBD
Chae, Y., et al. MR Damper Characterization – Lehigh – Damper 1
www.nees.org DOI – TBD
Chae, Y., et al. MR Damper Characterization – Lehigh – Damper 2
www.nees.org DOI - TBD
• System Identification Tests
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Ozdagli, A., et al. Dynamic Identification of the DBF – Lehigh
www.nees.org DOI - TBD
• Real Time Hybrid Tests
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Friedman, A., et al., Control Validation for 3-Story Prototype Structure - Single
MR Damper - www.nees.org DOI – TBD
Friedman, A., et al., Control Validation for 9-Story Benchmark Structure Single MR Damper - www.nees.org DOI - TBD
Friedman, A., et al., Control Validation for 9-Story Benchmark Structure - Two
MR Dampers - www.nees.org DOI – TBD
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Acknowledgements
• The researchers involved in this project wish to thank
the following:
▫ The National Science Foundation
 CMMI Grant # - 1011534
▫ George E. Brown Jr. Network for Earthquake
Engineering Simulation (NEES)
▫ NEES@Lehigh and NEES@UIUC Personnel
Thank you for your time!
Questions?