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Applied Computational Intelligence and Soft Computing
Volume 2016, Article ID 5241279, 12 pages
http://dx.doi.org/10.1155/2016/5241279
Research Article

A SVR Learning Based Sensor Placement Approach for Nonlinear Spatially Distributed Systems

1Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics and Automation, Shanghai University, Shanghai 200072, China
2Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China

Received 29 August 2016; Accepted 27 September 2016

Academic Editor: Wu Deng

Copyright © 2016 Xian-xia Zhang 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. P. D. Christofides, Nonlinear and Robust Control of Partial Differential Equation Systems: Methods and Applications to Transport-reaction Processes, Birkhäuser, Boston, Mass, USA, 2001. View at Publisher · View at Google Scholar · View at MathSciNet
  2. C. K. Qi, H.-X. Li, S. Y. Li, X. Zhao, and F. Gao, “A fuzzy-based spatio-temporal multi-modeling for nonlinear distributed parameter processes,” Applied Soft Computing, vol. 25, pp. 309–321, 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. H.-X. Li and C. K. Qi, “Modeling of distributed parameter systems for applications—a synthesized review from time-space separation,” Journal of Process Control, vol. 20, no. 8, pp. 891–901, 2010. View at Publisher · View at Google Scholar · View at Scopus
  4. A. Rensfelt, S. Mousavi, and M. Mossberg, “Optimal sensor locations for nonparametric identification of viscoelastic materials,” Automatica, vol. 44, no. 1, pp. 28–38, 2008. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  5. D. Ucinski, “Optimal sensor location for parameter estimation of distributed processes,” International Journal of Control, vol. 73, no. 13, pp. 1235–1248, 2000. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  6. A. Armaou and M. A. Demetriou, “Optimal actuator/sensor placement for linear parabolic PDEs using spatial H2 norm,” Chemical Engineering Science, vol. 61, no. 22, pp. 7351–7367, 2006. View at Publisher · View at Google Scholar · View at Scopus
  7. A. A. Alonso, I. G. Kevrekidis, J. R. Banga, and C. E. Frouzakis, “Optimal sensor location and reduced order observer design for distributed process systems,” Computers and Chemical Engineering, vol. 28, no. 1-2, pp. 27–35, 2004. View at Publisher · View at Google Scholar · View at Scopus
  8. I. Bruant, L. Gallimard, and S. Nikoukar, “Optimal piezoelectric actuator and sensor location for active vibration control, using genetic algorithm,” Journal of Sound and Vibration, vol. 329, no. 10, pp. 1615–1635, 2010. View at Publisher · View at Google Scholar · View at Scopus
  9. C. Antoniades and P. D. Christofides, “Integrating nonlinear output feedback control and optimal actuator/sensor placement for transport-reaction processes,” Chemical Engineering Science, vol. 56, no. 15, pp. 4517–4535, 2001. View at Google Scholar · View at Scopus
  10. C. Antoniades and P. D. Christofides, “Integrated optimal actuator/sensor placement and robust control of uncertain transport-reaction processes,” Computers and Chemical Engineering, vol. 26, no. 2, pp. 187–203, 2002. View at Publisher · View at Google Scholar · View at Scopus
  11. Y. Lou and P. D. Christofides, “Optimal actuator/sensor placement for nonlinear control of the kuramoto-sivashinsky equation,” IEEE Transactions on Control Systems Technology, vol. 11, no. 5, pp. 737–745, 2003. View at Publisher · View at Google Scholar · View at Scopus
  12. V. A. Wouwer, N. Point, S. Porteman, and M. Remy, “Approach to the selection of optimal sensor locations in distributed parameter systems,” Journal of Process Control, vol. 10, no. 4, pp. 291–300, 2000. View at Publisher · View at Google Scholar · View at Scopus
  13. E. Zamprogna, M. Barolo, and D. E. Seborg, “Optimal selection of soft sensor inputs for batch distillation columns using principal component analysis,” Journal of Process Control, vol. 15, no. 1, pp. 39–52, 2005. View at Publisher · View at Google Scholar · View at Scopus
  14. P. Tongpadungroda, T. D. L. Rhysb, and P. N. Brettc, “An approach to optimise the critical sensor locations in one-dimensional novel distributive tactile surface to maximise performance,” Sensors and Actuators, A: Physical, vol. 105, no. 1, pp. 47–54, 2003. View at Publisher · View at Google Scholar · View at Scopus
  15. X.-X. Zhang, H.-X. Li, and C.-K. Qi, “Spatially constrained fuzzy-clustering based sensor placement for spatio-temporal fuzzy-control system,” IEEE Transactions on Fuzzy Systems, vol. 18, no. 5, pp. 946–957, 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. R. N. Silva, J. M. Lemos, and L. M. Rato, “Variable sampling adaptive control of a distributed collector solar field,” IEEE Transactions on Control Systems Technology, vol. 11, no. 5, pp. 765–772, 2003. View at Publisher · View at Google Scholar · View at Scopus
  17. P. D. Christofides, “Robust control of parabolic PDE systems,” Chemical Engineering Science, vol. 53, no. 16, pp. 2949–2965, 1998. View at Publisher · View at Google Scholar · View at Scopus
  18. J. J. Winkin, D. Dochain, and P. Ligarius, “Dynamical analysis of distributed parameter tubular reactors,” Automatica, vol. 36, no. 3, pp. 349–361, 2000. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  19. K. A. Hoo and D. Zheng, “Low-order control-relevant models for a class of distributed parameter systems,” Chemical Engineering Science, vol. 56, no. 23, pp. 6683–6710, 2001. View at Publisher · View at Google Scholar · View at Scopus
  20. V. N. Vapnik, Statistical Learning Theory, John Wiley & Sons, New York, NY, USA, 1998. View at MathSciNet
  21. R. Haber and L. Keviczky, Nonlinear System Identification—Input-Output Modeling Approach, Volume 1: Nonlinear System Parameter Identification, Kluwer Academic Publishers, Dordrecht, The Netherlands, 1999.
  22. W. E. Schiesser, The Numerical Methods of Lines Integration of Partial Differential Equations, Academic Press, San Diego, Calif, USA, 1991. View at MathSciNet
  23. H.-X. Li, X.-X. Zhang, and S.-Y. Li, “A three-dimensional fuzzy control methodology for a class of distributed parameter systems,” IEEE Transactions on Fuzzy Systems, vol. 15, no. 3, pp. 470–481, 2007. View at Publisher · View at Google Scholar · View at Scopus
  24. X.-X. Zhang, H.-X. Li, and S.-Y. Li, “Analytical study and stability design of a 3-D fuzzy logic controller for spatially distributed dynamic systems,” IEEE Transactions on Fuzzy Systems, vol. 16, no. 6, pp. 1613–1625, 2008. View at Publisher · View at Google Scholar · View at Scopus
  25. C. B. Kellogg and F. Zhao, “Influence-based model decomposition for reasoning about spatially distributed physical systems,” Artificial Intelligence, vol. 130, no. 2, pp. 125–166, 2001. View at Publisher · View at Google Scholar · View at Scopus
  26. X.-X. Zhang, S. Y. Li, and H.-X. Li, “Decomposition-coordination-based fuzzy logic control for spatially distributed systems,” Control and Decision, vol. 23, no. 6, pp. 709–713, 2008. View at Google Scholar