Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2015, Article ID 361581, 10 pages
http://dx.doi.org/10.1155/2015/361581
Research Article

Information Fusion Based Decoupling Control for Multivariable Nonlinear System

College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Received 26 April 2014; Revised 10 December 2014; Accepted 10 December 2014

Academic Editor: Sebastian Anita

Copyright © 2015 Ziyang Zhen 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. G. Tao, X. Ma, and Y. Ling, “Optimal and nonlinear decoupling control of systems with sandwiched backlash,” Automatica, vol. 37, no. 2, pp. 165–176, 2001. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  2. H. J. Huijberts, C. H. Moog, and R. Pothin, “Input-output decoupling of nonlinear systems by static measurement feedback,” Systems & Control Letters, vol. 39, no. 2, pp. 109–114, 2000. View at Publisher · View at Google Scholar · View at MathSciNet
  3. R.-J. Lian and B.-F. Lin, “Design of a mixed fuzzy controller for multiple-input multiple-output systems,” Mechatronics, vol. 15, no. 10, pp. 1225–1252, 2005. View at Publisher · View at Google Scholar · View at Scopus
  4. T. Liu, W. D. Zhang, and D. Y. Gu, “Analytical design of decoupling internal model control (IMC) scheme for two-input-two-output (TITO) process with time delays,” Industrial & Engineering Chemistry, vol. 45, no. 9, pp. 3149–3160, 2006. View at Google Scholar
  5. T. Liu, W. Zhang, and F. Gao, “Analytical decoupling control strategy using a unity feedback control structure for MIMO processes with time delays,” Journal of Process Control, vol. 17, no. 2, pp. 173–186, 2007. View at Publisher · View at Google Scholar · View at Scopus
  6. Z. Wang, Z. Chen, Q. Sun, and Z. Yuan, “Multivariable decoupling predictive control based on QFT theory and application in CSTR chemical process,” Chinese Journal of Chemical Engineering, vol. 14, no. 6, pp. 765–769, 2006. View at Publisher · View at Google Scholar · View at Scopus
  7. S. Liu, X. Mei, F. Kong, and K. He, “A decoupling control algorithm for unwinding tension system based on active disturbance rejection control,” Mathematical Problems in Engineering, vol. 2013, Article ID 439797, 18 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus
  8. Y. Xie, Y. Tan, and R. Dong, “Nonlinear modeling and decoupling control of XY micropositioning stages with piezoelectric actuators,” IEEE/ASME Transactions on Mechatronics, vol. 18, no. 3, pp. 821–832, 2013. View at Publisher · View at Google Scholar · View at Scopus
  9. F. E. White, “A model for data fusion,” in Proceedings of the 1st National Symposium on Sensor Fusion, vol. 2, pp. 5–8, Orlando, Fla, USA, 1988.
  10. A. N. Steinberg, L. C. Bowman, and E. F. White, “Revisions to the JDL data fusion model,” in Proceedings of SPIE. Sensor Fusion: Architectures, Algorithms, and Applications, pp. 430–441, Orlando: Fla, USA, 1999.
  11. N. A. Carlson, “Federated square root filter for decentralized parallel processes,” IEEE Transactions on Aerospace and Electronic Systems, vol. 26, no. 3, pp. 517–525, 1990. View at Publisher · View at Google Scholar · View at Scopus
  12. K. H. Kim, “Development of track to track fusion algorithm,” in Proceedings of the American Control Conference, pp. 1037–1041, 1994.
  13. A. G. O. Mutambara, “Information based estimation for both linear and nonlinear systems,” in Proceedings of the American Control Conference, pp. 1329–1333, San Diego, Calif, USA, 1999.
  14. X. Li, Y. Zhu, J. Wang, and C. Han, “Optimal linear estimation fusion—part I: unified fusion rules,” IEEE Transactions on Information Theory, vol. 49, no. 9, pp. 2192–2323, 2003. View at Publisher · View at Google Scholar · View at Scopus
  15. Y. Zhu, X. Li, and J. Zhao, “Linear minimum variance estimation fusion,” Science in China Series F: Information Sciences, vol. 47, no. 6, pp. 728–740, 2004. View at Google Scholar · View at MathSciNet · View at Scopus
  16. S. Sun and Z. Deng, “Multi-sensor optimal information fusion Kalman filter,” Automatica, vol. 40, no. 6, pp. 1017–1023, 2004. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  17. J. Zhou, Z. Wang, and F. Zhou, “Theory of multi-sensor system data fusion based on linear least square estimation,” Journal of Astronautics, vol. 24, no. 4, pp. 364–367, 2003. View at Google Scholar · View at Scopus
  18. Z. Wang, D. Wang, and Z. Zhen, “Primary exploration of nonlinear information fusion control theory,” Science in China, Series F: Information Sciences, vol. 50, no. 5, pp. 686–696, 2007. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  19. Z. Zhen, Z. Wang, and Z. Hu, “Information fusion based solving method for linear quadratic optimal control problem,” in Proceedings of the 7th IEEE International Conference on Control & Automation (ICCA '09), pp. 727–731, Christchurch, New Zealand, December 2009.
  20. Z. Zhen, D. Wang, and Q. Kang, “UAV flight trajectory control based on information fusion control method,” in Proceedings of the IEEE International Conference on Networking, Sensing and Control, pp. 337–341, Chicago, Ill, USA, April 2010.
  21. Z. Zhen, J. Jiang, X. Wang, and D. Wang, “Information fusion-based optimal attitude control for an alterable thrust direction unmanned aerial vehicle,” International Journal of Advanced Robotic Systems, vol. 10, no. 43, pp. 1–9, 2013. View at Google Scholar
  22. F. Ding, “Several multi-innovation identification methods,” Digital Signal Processing: A Review Journal, vol. 20, no. 4, pp. 1027–1039, 2010. View at Publisher · View at Google Scholar · View at Scopus
  23. F. Ding and Y. Gu, “Performance analysis of the auxiliary model-based least-squares identification algorithm for one-step state-delay systems,” International Journal of Computer Mathematics, vol. 89, no. 15, pp. 2019–2028, 2012. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus