Transcript Structural Control II - Smart Structures Technology Laboratory

Asia-Pacific Student Summer School on Smart Structures Technology
KAIST, Daejeon, Korea
August 1, 2008
Day 2.
Lecturers: H.-J. Jung, H. Myung, KAIST, Korea
Assistants: S.H. Park, D.D. Jang, KAIST, Korea
Lab. Schedule
Time
8/1 (Fri)
13:00-17:00*
Topics
Demonstration: MR damper-based semi-active
control
 Lab.: Active control using piezo-actuator
 Introduction to student competition:
Project II: Structural Control
*Group 1: 13:00-15:00
Group 2: 15:00-17:00
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MR Damper-based Semiactive Control System
 Experimental Setup
3
MR Damper-based Semiactive Control System
 Control Algorithm: Modal Neuro Control
4
MR Damper-based Semiactive Control System
 Experimental Test Results
5
MR Damper-based Semiactive Control System
 Experimental Test Results
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Active Control Using PiezoActuator
 Experimental Setup
PZT actuator
PZT sensor
Notebook
DAQ Terminal block
Power Amplifier
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Active Control Using PiezoActuator
 Experimental Setup
 Structure
 Cantilever beam made of aluminum (500(L) ⅹ 50(W) ⅹ 0.8(t) (mm))
 Sensor, Compensator & Exciter
 Piezoceramic patch
 Data Acquisition & Real Time Control
 Hardware: NI DAQCard-6062E for PCMCIA & Terminal Block BNC-2110
 Software: MATLAB Real Time Workshop
 Other Equipments
 Power Amplifier (or High Voltage Amplifier)
 Control Algorithm for active control
 Positive Position Feedback (PPF) Control (sample controller)
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Active Control Using PiezoActuator
 Sample Control Algorithm: PPF Control
The equation of motion of the beam:
My  Cy  Ky  Lu
where,
(1)
M, C, K : mass, damping, stiffness matrix of the beam
y(x,t) : displacement at the position y and time t
u : control input
L: the location defining vector for u
The y(x,t) can be rewritten as the product of mode shape φ(x) and modal coordinate q(t).
M q  C q  K q  Lu
→
 T M q   T C q   T K q   T Lu
Since, it is orthogonal among the modes, the equation of motion can be written as follows:
qi  2 ii qi  i2 qi  Leui
where,
, 
: damping ratio and natural frequency of the beam.
(2)
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Active Control Using PiezoActuator
 Sample Control Algorithm: PPF Control
The control input u is generated by the PPF control scheme as
u  H ̂
Where,
̂
(3)
is the output vector from a set of PPF filters described as
ˆ  2 ccˆ  c2ˆ  c2 q
where,
(4)
c ,  c : the PPF filter frequency and damping ratio.
Then, the equation (2) can be rewritten as
qi  2 ii qi  i2 qi  Le Hˆ
Since, Le H is square matrix, let’s define a new signal
gi2   Le Hˆ
where, g is the control gain.
(5)
 , which satisfies
(6)
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Active Control Using PiezoActuator
 Sample Control Algorithm: PPF Control
The resultant closed-loop system can be written as
qi  2 ii qi  i2 qi  gi2 
(7)
  2 cc  c2  c2 q
(8)
qi  2 ii qi   qi  0
2
i
g
qi
structure
2
i

c2
  2 cc  c2  0
compensator
< The block diagram of PPF controller >
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Active Control Using PiezoActuator
 MATLAB Simulink Block for Experiment
1
Analog
Input
2
Analog Input
National Instruments
DAQCard-6062E [auto]
PZT sensor
-K-
x' = Ax+Bu
y = Cx+Du
control gain
4
PPF control
3
5
PZT actuator
Sine Wave1
0
Constant
Analog
Output
0
Clock3
0
Clock2
0
Clock1
Analog Output
Switch3
National Instruments
DAQCard-6062E [auto]
Switch2
Sine Wave
Switch1
6
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Active Control Using PiezoActuator
 MATLAB Simulink Block for Experiment
① The voltage generated by PZT sensor is acquired through the DAQ card.
② PPF controller, which calculates the required control voltage.
③ If 0≤ time ≤ 20s, sine wave, else zero voltage will be provided.
④ If time ≤ 45s, the voltage determined by ③, else sine wave1 voltage will be provided.
⑤ If time ≤ 60s, the voltage determined by ④, else the voltage calculated by PPF
controller will be provided.
⑥ The voltage determined by ⑤ will provided to the PZT actuator through the DAQ card.
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Asia-Pacific Student Summer School on Smart Structures Technology
KAIST, Daejeon, Korea
July 28-August 16, 2008
Student Competition
Project 1: Structural Monitoring
Lecturers: J.-J. Lee, Sejong Univ., K.Y. Koo, KAIST, Korea
Assistants: H.J. Park, H.J. Kim, KAIST, Korea
Student Competition
Project 1: Structural Monitoring
 Problem Description
Problems
Prob. 1
Prob. 2
Description
Damage detection on a steel beam
- All data sets including baseline and 3 unknown
states will be provided.
- Identify damage existence, location and severity if
possible.
- You CAN use ANY algorithm and software, not
limited to the peak-picking method and IDIS.
Monitoring of model structures
- Make each team’s own structure using pieces of
steel beams which are provided.
- Establish monitoring strategies fit to each structure.
- Introduce damages
- Perform vibration tests and damage identification
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Student Competition
Project 1: Structural Monitoring
 Evaluation Criteria*
Problems
Prob. 1
(50%)
Evaluation Criteria
 Damage identification results for 3 unknown data sets
 Programming skills for demonstration
 New methodologies (probably) will get additional points
Prob. 2
(50%)
 Novelty of problem definition (structure, damage type,
algorithms, etc.)
 Completeness of procedures
 Presentation/Demonstration skills
 Teamwork
* Final evaluation criteria will be announced on 8/6 (Wed).
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Asia-Pacific Student Summer School on Smart Structures Technology
KAIST, Daejeon, Korea
July 28-August 16, 2008
Student
Competition
Prjoect 2: Structural Control
Lecturers: H.-J. Jung, H. Myung, KAIST, Korea
Assistants: S.-H. Park, D.-D. Jang, KAIST, Korea
Student Competition
Project 2: Structural Control
 Problem Description
Problems
Prob. 1
Prob. 2
Description
Vibration control of cantilever beam using
piezo-actuator
- Strain-rate feedback (SRF) control algorithm
- SRF control algorithm can be obtained by slightly
modifying PPF control algorithm.
Vibration control of cantilever beam using
piezo-actuator
- Any control algorithm can be used
- Neuro-control and fuzzy control are recommended
* New specimens for student competition will be distributed on 8/6 (Wed).
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Student Competition
Project 2: Structural Control
 Evaluation Criteria*
Problems
Prob. 1
(40%)
Evaluation Criteria
 Damping ratio (50%)
 Settling time (5% of the initial value) (30%)
 Overshooting (20%)
Prob. 2
(40%)
 Completeness of control algorithm (40%)
 Damping ratio (30%)
 Settling time (5% of the initial value) (20%)
 Overshooting (10%)
Presentation
(20%)
 Presentation and demonstration skills
 Teamwork
* Final evaluation criteria will be announced on 8/6 (Wed).
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