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Shock and Vibration
Volume 2017, Article ID 1427270, 18 pages
https://doi.org/10.1155/2017/1427270
Research Article

An Observer-Based Controller with a LMI-Based Filter against Wind-Induced Motion for High-Rise Buildings

1School of Civil and Environment Engineering, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, China
2Department of Civil and Environmental Engineering, University of Surrey, Guildford GU2 7XH, UK

Correspondence should be addressed to Zuo-Hua Li; nc.ude.tih@auhouzil

Received 23 December 2016; Revised 21 March 2017; Accepted 11 April 2017; Published 25 May 2017

Academic Editor: Jiming Xie

Copyright © 2017 Chao-Jun Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. H. Cao, A. M. Reinhorn, and T. T. Soong, “Design of an active mass damper for a tall TV tower in Nanjing, China,” Engineering Structures, vol. 20, no. 3, pp. 134–143, 1998. View at Publisher · View at Google Scholar · View at Scopus
  2. M. Yamamoto, S. Aizawa, M. Higashino, and K. Toyama, “Practical applications of active mass dampers with hydraulic actuator,” Earthquake Engineering and Structural Dynamics, vol. 30, no. 11, pp. 1697–1717, 2001. View at Publisher · View at Google Scholar · View at Scopus
  3. F. Ricciardelli, A. D. Pizzimenti, and M. Mattei, “Passive and active mass damper control of the response of tall buildings to wind gustiness,” Engineering Structures, vol. 25, no. 9, pp. 1199–1209, 2003. View at Publisher · View at Google Scholar · View at Scopus
  4. Y. Ikeda, K. Sasaki, M. Sakamoto, and T. Kobori, “Active mass driver system as the first application of active structural control,” Earthquake Engineering and Structural Dynamics, vol. 30, no. 11, pp. 1575–1595, 2001. View at Publisher · View at Google Scholar · View at Scopus
  5. B. Basu, O. S. Bursi, F. Casciati et al., “A European association for the control of structures joint perspective. recent studies in civil structural control accross europe,” Structural Control and Health Monitoring, vol. 21, no. 12, pp. 1414–1436, 2014. View at Publisher · View at Google Scholar
  6. J. Teng, H. B. Xing, Y. Q. Xiao, C. Y. Liu, H. Li, and J. P. Ou, “Design and implementation of AMD system for response control in tall buildings,” Smart Structures and Systems, vol. 13, no. 2, pp. 235–255, 2014. View at Publisher · View at Google Scholar · View at Scopus
  7. J. Teng, H. B. Xing, W. Lu, Z. H. Li, and C. J. Chen, “Influence analysis of time delay to active mass damper control system using pole assignment method,” Mechanical Systems and Signal Processing, vol. 80, pp. 99–116, 2016. View at Publisher · View at Google Scholar · View at Scopus
  8. H. Kheloufi, A. Zemouche, F. Bedouhene, and M. Boutayeb, “A new observer-based stabilization method for linear systems with uncertain parameters,” in Proceedings of the European Control Conference (ECC '13), pp. 1120–1125, Zurich, Switzerland, July 2013. View at Scopus
  9. H. R. Karimi and M. Chadli, “Robust observer design for takagi-sugeno fuzzy systems with mixed neutral and discrete delays and unknown inputs,” Mathematical Problems in Engineering, vol. 2012, Article ID 635709, 13 pages, 2012. View at Publisher · View at Google Scholar · View at Scopus
  10. A. Golabi, M. T. Beheshti, and M. H. Asemani, “Dynamic observer-based controllers for linear uncertain systems,” Journal of Control Theory and Applications, vol. 11, no. 2, pp. 193–199, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  11. M. Farza, M. M'Saad, T. Maatoug, and M. Kamoun, “Adaptive observers for nonlinearly parameterized class of nonlinear systems,” Automatica. A Journal of IFAC, the International Federation of Automatic Control, vol. 45, no. 10, pp. 2292–2299, 2009. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  12. D. Saoudi, M. Chadli, C. Mechmeche, and N. Benhadj Braiek, “Unknown input observer design for fuzzy bilinear system: an LMI approach,” Mathematical Problems in Engineering, vol. 2012, Article ID 794581, 21 pages, 2012. View at Publisher · View at Google Scholar · View at Scopus
  13. D. Krokavec and A. Filasová, “A reduced-order TS fuzzy observer scheme with application to actuator faults reconstruction,” Mathematical Problems in Engineering, vol. 2012, Article ID 951953, 25 pages, 2012. View at Publisher · View at Google Scholar · View at Scopus
  14. D. Liu, Y. Huang, D. Wang, and Q. Wei, “Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming,” International Journal of Control, vol. 86, no. 9, pp. 1554–1566, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  15. N. Boizot, E. Busvelle, and J.-P. Gauthier, “An adaptive high-gain observer for nonlinear systems,” Automatica. A Journal of IFAC, the International Federation of Automatic Control, vol. 46, no. 9, pp. 1483–1488, 2010. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  16. S. Jeon and M. Tomizuka, “Benefits of acceleration measurement in velocity estimation and motion control,” Control Engineering Practice, vol. 15, no. 3, pp. 325–332, 2007. View at Publisher · View at Google Scholar · View at Scopus
  17. F. Qin, X. Dai, and J. E. Mitchell, “Effective-SNR estimation for wireless sensor network using Kalman filter,” Ad Hoc Networks, vol. 11, no. 3, pp. 944–958, 2013. View at Publisher · View at Google Scholar · View at Scopus
  18. A. Alessandri, M. Baglietto, and G. Battistelli, “A maximum-likelihood Kalman filter for switching discrete-time linear systems,” Automatica. A Journal of IFAC, the International Federation of Automatic Control, vol. 46, no. 11, pp. 1870–1876, 2010. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  19. M. Karasalo and X. Hu, “An optimization approach to adaptive Kalman filtering,” Automatica. A Journal of IFAC, the International Federation of Automatic Control, vol. 47, no. 8, pp. 1785–1793, 2011. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  20. R. Peesapati, S. L. Sabat, K. P. Karthik, J. Nayak, and N. Giribabu, “Efficient hybrid Kalman filter for denoising fiber optic gyroscope signal,” Optik, vol. 124, no. 20, pp. 4549–4556, 2013. View at Publisher · View at Google Scholar · View at Scopus
  21. Z. Liu, J. Wang, and Y. Xue, “Interacting multiple sensor filter,” Signal Processing, vol. 92, no. 9, pp. 2180–2186, 2012. View at Publisher · View at Google Scholar · View at Scopus
  22. Y. H. Yu, “Combining H filter and cost-reference particle filter for conditionally linear dynamic systems in unknown non-Gaussian noises,” Signal Processing, vol. 93, no. 7, pp. 1871–1878, 2013. View at Publisher · View at Google Scholar · View at Scopus
  23. W. J. Qi, P. Zhang, and Z. L. Deng, “Robust weighted fusion Kalman filters for multisensor time-varying systems with uncertain noise variances,” Signal Processing, vol. 99, no. 1, pp. 185–200, 2014. View at Publisher · View at Google Scholar · View at Scopus
  24. B. Fridholm, T. Wik, and M. Nilsson, “Kalman filter for adaptive learning of look-up tables with application to automotive battery resistance estimation,” Control Engineering Practice, vol. 48, pp. 78–86, 2016. View at Publisher · View at Google Scholar · View at Scopus
  25. F. Alonge, F. D'Ippolito, A. Fagiolini, and A. Sferlazza, “Extended complex Kalman filter for sensorless control of an induction motor,” Control Engineering Practice, vol. 27, no. 1, pp. 1–10, 2014. View at Publisher · View at Google Scholar · View at Scopus
  26. O. Rosén, A. Medvedev, and T. Wigren, “Parallelization of the Kalman filter on multicore computational platforms,” Control Engineering Practice, vol. 21, no. 9, pp. 1188–1194, 2013. View at Publisher · View at Google Scholar · View at Scopus
  27. S. W. Pan, H. Y. Su, J. Chu, and H. Wang, “Applying a novel extended Kalman filter to missile-target interception with APN guidance law: A benchmark case study,” Control Engineering Practice, vol. 18, no. 2, pp. 159–167, 2010. View at Publisher · View at Google Scholar · View at Scopus
  28. S. Boyd, L. E. Ghaoui, E. Feron, and V. Balakrishnan, Linear matrix inequalities in system and control theory, vol. 15 of SIAM Studies in Applied Mathematics, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, Pa, USA, 1994. View at Publisher · View at Google Scholar · View at MathSciNet
  29. L. Yu, Robust Control-Linear Matrix Inequalities Approach, Tsinghua University Press, China, 2002.
  30. C. X. Qu, L. S. Huo, and H. N. Li, “Fault tolerant control for civil structures based on LMI approach,” Mathematical Problems in Engineering, vol. 2013, Article ID 762385, 8 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus
  31. E. J. Hannan, “The identification of vector mixed autoregressive-moving average system,” Biometrika, vol. 56, pp. 223–225, 1969. View at Publisher · View at Google Scholar · View at MathSciNet
  32. J. P. Ou, Active, Semi-Active and Intelligent Control in Civil Engineering Structure, Science Press, 2003.
  33. G. Burgers, P. J. van Leeuwen, and G. Evensen, “Analysis scheme in the ensemble Kalman filter,” Monthly Weather Review, vol. 126, no. 6, pp. 1719–1724, 1998. View at Publisher · View at Google Scholar · View at Scopus
  34. R. F. Souto and J. Y. Ishihara, “Robust kalman filter for discrete-time systems with correlated noises,” in Proceedings od the Mediterranean Conference on Control and Automation, (MED '08), pp. 1658–1662, fra, June 2008. View at Publisher · View at Google Scholar · View at Scopus
  35. J.-H. Ge, P. M. Frank, and C.-F. Lin, “Robust H state feedback control for linear systems with state delay and parameter uncertainty,” Automatica, vol. 32, no. 8, pp. 1183–1185, 1996. View at Publisher · View at Google Scholar · View at MathSciNet
  36. R. Panigrahi and B. Subudhi, “Performance enhancement of shunt active power filter using a Kalman filter based H control strategy,” IEEE Transactions on Power Electronics, pp. 1–9, 2016. View at Publisher · View at Google Scholar