1. Day 2. Lecturers: H.-J. Jung, H. Myung, KAIST, Korea Assistants: S.H. Park, D.D. Jang, KAIST, Korea Asia-Pacific Student Summer School on Smart Structures Technology KAIST, Daejeon, Korea August 1, 2008

2. 2 Lab. Schedule TimeTopics 8/1 (Fri) 13:00-17:00* 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

3. MR Damper-based Semi- active Control System 3 Experimental Setup

4. 4 Control Algorithm: Modal Neuro Control MR Damper-based Semi- active Control System

5. 5 Experimental Test Results

6. 6 MR Damper-based Semi- active Control System

7. Active Control Using Piezo- Actuator Experimental Setup 7 Notebook DAQ Terminal block Power Amplifier PZT actuator PZT sensor

8. 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) Active Control Using Piezo- Actuator 8 Experimental Setup

9. 9 The equation of motion of the beam: where, M, C, K : mass, damping, stiffness matrix of the beam y(x,t) : displacement at the position y and time t u : control inputL: 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). → Since, it is orthogonal among the modes, the equation of motion can be written as follows: where, : damping ratio and natural frequency of the beam. (1) (2) Active Control Using Piezo- Actuator Sample Control Algorithm: PPF Control

10. 10 The control input u is generated by the PPF control scheme as Where, is the output vector from a set of PPF filters described as where, : the PPF filter frequency and damping ratio. Then, the equation (2) can be rewritten as Since, is square matrix, let’s define a new signal, which satisfies where, g is the control gain. (3) (4) (5) (6) Active Control Using Piezo- Actuator Sample Control Algorithm: PPF Control

11. 11 The resultant closed-loop system can be written as (7) (8) structure compensator Active Control Using Piezo- Actuator Sample Control Algorithm: PPF Control

12. 12 1 3 4 5 6 2 Active Control Using Piezo- Actuator MATLAB Simulink Block for Experiment

13. 13 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. Active Control Using Piezo- Actuator MATLAB Simulink Block for Experiment

14. 14

15. 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 Asia-Pacific Student Summer School on Smart Structures Technology KAIST, Daejeon, Korea July 28-August 16, 2008

16. Student Competition Project 1: Structural Monitoring 16 ProblemsDescription Prob. 1 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. Prob. 2 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 Problem Description

17. 17 ProblemsEvaluation Criteria Prob. 1 (50%) 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 Evaluation Criteria* * Final evaluation criteria will be announced on 8/6 (Wed). Student Competition Project 1: Structural Monitoring

18. Student Competition Prjoect 2: Structural Control Lecturers: H.-J. Jung, H. Myung, KAIST, Korea Assistants: S.-H. Park, D.-D. Jang, KAIST, Korea Asia-Pacific Student Summer School on Smart Structures Technology KAIST, Daejeon, Korea July 28-August 16, 2008

19. Student Competition Project 2: Structural Control 19 ProblemsDescription Prob. 1 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. Prob. 2 Vibration control of cantilever beam using piezo-actuator - Any control algorithm can be used - Neuro-control and fuzzy control are recommended Problem Description * New specimens for student competition will be distributed on 8/6 (Wed).

20. 20 ProblemsEvaluation Criteria Prob. 1 (40%) 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 Student Competition Project 2: Structural Control Evaluation Criteria* * Final evaluation criteria will be announced on 8/6 (Wed).