Journal of the Earthquake Engineering Society of Korea (한국지진공학회논문집)

Earthquake Engineering Society of Korea (한국지진공학회)
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Control of Smart Base-isolated Benchmark Building using Fuzzy Supervisory Control

퍼지관리제어기법을 이용한 스마트 면진 벤치마크 건물의 제어

  • 김현수 (성균관대학교 건축공학과) ;
  • Published : 2005.08.01
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Abstract

The effectiveness of fuzzy supervisory control technique for the control of seismic responses of smart base isolation system is investigated in this study. To this end, first generation base isolated building benchmark problem is employed for the numerical simulation. The benchmark structure under consideration is an eight-story base isolated building having irregular plan and is equipped with low-damping elastometric bearings and magnetorheological (MR) dampers for seismic protection. Lower level fuzzy logic controllers (FLC) for far-fault or near-fault earthquakes are developed in order to effectively control base isolated building using multi-objective genetic algorithm. Four objectives, i.e. reduction of peak structural acceleration, peak base drift, RMS structural acceleration and RMS base drift, are used in multi-objective optimization process. When earthquakes are applied to benchmark building, each of low level FLCs provides different command voltage and supervisory fuzzy controller combines two command voltages io one based on fuzzy inference system in real time. Results from the numerical simulations demonstrate that base drift as well as superstructure responses can be effectively reduced using the proposed supervisory fuzzy control technique.

본 논문에서는 스마트 면진장치를 효과적으로 제어하기 위하여 퍼지관리제어기를 개발하였고 그 효율성을 검토하였다. 이를 위하여 1세대 스마트 면진 벤치마크 건물을 이용하여 수치해석을 수행하였다. 대상 벤치마크 구조물은 부정형의 평면을 가지고 있는 8층 건물이고 탄성베어링과 MR 감쇠기로 이루어진 스마트 면진장치가 설치되어 있다. 본 논문에서는 다목적 유전자 알고리즘을 이용하여 원거리 지진과 근거리 지진에 대하여 각각 면진구조물을 효과적으로 제어할 수 있는 하위 퍼지제어기를 개발한다. 최적화과정에서는 구조물의 최대 및 RMS 가속도와 면진층 변위의 저감이 목적으로 사용된다. 벤지마크 건물에 지진하중이 가해지면 두 개의 하위 퍼지제어기에서는 각각 다른 명령전압이 제공되는데 이 명령전압들은 퍼지관리제어기의 추론과정에 기반하여 실시간으로 참여율이 조절되어 하나의 명령전압으로 조합된다. 수치해석을 통하여 제안된 퍼지관리제어기법을 사용함으로써 상부구조물의 응답과 면진층의 변위를 효과적으로 줄일 수 있음을 확인할 수 있다.

Keywords

References

  1. Hall J.F., Heaton T.H., Halling M.W. and Wald D.J., 'Near-source ground motion and its effects on flexible buildings,' Earthquake Spectra, Vol. 11, No. 4, 1995, pp. 569-605 https://doi.org/10.1193/1.1585828
  2. Heaton T.H., Hall J.F., Wald D.J. and Halling M.W., 'Response of high-rise and base-isolated buildings in a hypothetical Mw 7.0 blind thrust earthquake,' Science, Vol. 267, 1995, pp. 206-211 https://doi.org/10.1126/science.267.5195.206
  3. Kelly, J.M., 'The role of damping in seismic isolation,' Earthquake Eng. Struct. Dyn. Vol. 28, 1999, pp. 30-20
  4. Kelly, J.M., 'The current state of base isolation in the Unite States,' Proc. Second World Conference on Structural Control, Kyoto, Japan, Vol. 1, 1999, pp. 1043-1052
  5. Spencer, B.F. Jr, Johnson, E.A. and Ramallo, J.C., 'Smart isolation for seismic control,' JSME Int. J. Ser. C., Vol. 43, No. 4, 2000, pp. 704-711
  6. Johnson, E.A., Ramallo, J.C., Spencer, B.F. Jr and Sain M.K., 'Intelligent base isolation systems,' Proc. 2nd World Canf. on Structural Control, Kyoto, Japan, 1999, pp. 367-376
  7. Narasimhan, S., Nagarajaiah, S., Hohnson, E.A. and Gavin H.P., 'Smart base isolated benchmark building part I: problem definition,' J. of Struct. Control and Health Monitoring, 2004, in review
  8. Narasimhan, S. and Nagarajaiah S., 'Phase I smart base isolated benchmark building - sample controllers for linear isolation system: part II,' J. of Struct. Control and Health Monitoring, 2004, in review
  9. 정형조, 최강민, 장지은, 이인원, 'MR감쇠기가 설치된 지진격리 건물의 스마트 진동제어', 한국지진공학회 학술대회 논문집, 한국지진공학회, 2005, pp. 544-551
  10. 박관순, 고현무, 옥승용, 서충원, '퍼지관리제어기법을 이용한 사장교의 지진응답제어', 한국지진공학회 논문집, 8권, 4호, 2004, pp. 51-62
  11. 박관순, 고현무, 옥승용, '퍼지관리제어기법을 이용한 지진응답의 능동제어', 한국지진공학회 논문집, 5권, 4호, 2001, pp. 75-81
  12. Chekkouri, K., Romeral, L., Catala, J. and Aldabas, E., 'Supervisory fuzzy control of non-linear motion systems,' 7th Int. Workshop on Advanced Motion Control, Maribor, Slovenia, 2002, pp. 341-346
  13. Sbarbaro, D. and Segovia, J.P., 'Application of a supervisory fuzzy controller for controlling nonlinear processes,' Proc. of the Fifth IEEE Int. Conf. on Fuzzy Systems, New Orleans, LA, 1996, pp. 575-579
  14. Deb, K., Pratap, A., Agrawal, S. and Meyarivan, T., 'A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II,' Technical Report No. 200001, Kanpur: Indian Institute of Technology Kanpur, India, 2000
  15. Schaffer, J.D., 'Multiple objective optimization with vector evaluated genetic algorithms,' Proceedings of the First International Conference on Genetic Algorithms, Hillsdale, New Jersey, 1985, pp. 93-100
  16. Horn, J., Nafpliotis, N. and Goldberg, D.E., 'A niched Pareto genetic algorithm for multiobjective optimization,' Proceedings of the First IEEE Conference on Evolutionary Computation, IEEE Press, Orlando, FL, 1994, pp. 82-87
  17. Fonseca, C.M. and Fleming, P.J., 'Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization,' Genetic Algorithms: Proceedings of the Fifth International Conference, Morgan Kaufmann, San Mateo, CA, 1993, pp. 416-423
  18. Goldberg, D.E., Genetic Algorithms in Search, Optimization and Machine Learning, Reissue, Addison-Wesley Publishing Company, 1989
  19. Jangid, R.S. and Kelly, J.M., 'Base isolation for near-fault motions,' Earthquake Engrg. and Struct. Dyn., Vol. 30, 2001, pp. 691-707 https://doi.org/10.1002/eqe.31
  20. Jang, J.R., Sun, C.T. and Mizutani, E., Neuro-Fuzzy and Soft Computing, Prentice-Hall International, Inc., 1997, 343pp