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Parameter-dependent robust H filter design for uncertain discrete-time systems with quantized measurements

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  • Control Theory
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Abstract

This paper deals with the problem of parameter-dependent robust H filter design for uncertain discrete-time systems with output quantization. The uncertain parameters are supposed to reside in a polytope. The system outputs are quantized by a memoryless logarithmic quantizer before being transmitted to a filter. Attention is focused on the design of a robust H filter to mitigate quantization effects and ensure a prescribed H noise attenuation level. Via introducing some slack variables and using the parameter-dependent Lyapunov function, sufficient conditions for the existence of a robust H filter are expressed in terms of linear matrix inequalities (LMIs). Finally, a numerical example is provided to demonstrate the effectiveness of the proposed approach.

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References

  1. R. E. Kalman, “Nonlinear aspects of sampled-data control systems,” Proc. Symp. Nonlinear Circuit Theory, vol. VII, Brooklyn, NY, 1956.

  2. N. Elia and S. K. Mitter, “Stabilization of linear systems with limited information,” IEEE Trans. on Automatic Control, vol. 46, no. 9, pp. 1384–1400, Sep. 2001.

    Article  MathSciNet  MATH  Google Scholar 

  3. M. Fu and L. Xie, “The sector bound approach to quantized feedback control,” IEEE Trans. on Automatic Control, vol. 50, no. 11, pp. 1698–1711, Nov. 2005.

    Article  MathSciNet  Google Scholar 

  4. F. Fagnani and S. Zampieri, “Stability analysis and synthesis for scalar linear systems with a quantized feedback,” IEEE Trans. on Automatic Control, vol. 48, no. 9, pp. 1569–1584, Sep. 2003.

    Article  MathSciNet  Google Scholar 

  5. D. F. Delchamps, “Stabilizing a linear system with quantized state feedback,” IEEE Trans. on Automatic Control, vol. 35, no. 8, pp. 916–924, Aug. 1990.

    Article  MathSciNet  MATH  Google Scholar 

  6. H. Gao and T. Chen, “A new approach to quantized feedback control systems,” Automatica, vol. 44, no. 2, pp. 534–542, Feb. 2008.

    Article  MathSciNet  Google Scholar 

  7. B. Widrow, I. Kolla, and M. Liu, “Statical theory of quantization,” IEEE Trans. on Instrumentation and Measurement, vol. 45, no. 2, pp. 353–361, Apr. 1996.

    Article  Google Scholar 

  8. B. Zhou, G. R. Duan, and J. Lam, “On the absolute stability approach to quantized feedback control,” Automatica, vol. 46, no. 2, pp. 337–346, Feb. 2010.

    Article  MathSciNet  MATH  Google Scholar 

  9. K. You, W. Su, M. Fu, and L. Xie, “Attainability of the minimum data rate for stabilization of linear systems via logarithmic quantization,” Automatica, vol. 47, no. 1, pp. 170–176, Jan. 2011.

    Article  MathSciNet  MATH  Google Scholar 

  10. T. Liu, Z. Jiang, and D. Hill, “A sector bound approach to feedback control of nonlinear systems with state quantization,” Automatica, vol. 48, no. 1, pp. 145–152, Jan. 2012.

    Article  MathSciNet  MATH  Google Scholar 

  11. B. D. O. Anderson and J. B. Moore, Optimal Filtering, Prentice-Hall, Englewood Cliffs, NJ, 1979.

    MATH  Google Scholar 

  12. K. M. Nagpal and P. P. Khargonekar, “Filtering and smoothing in an H setting,” IEEE Trans. on Automatic Control, vol. 36, no. 2, pp. 152–166, Feb. 1991.

    Article  MathSciNet  MATH  Google Scholar 

  13. R. M. Palhares and P. L. D. Peres, “LMI approach to the mixed H 2/H filtering design for discretetime uncertain systems,” IEEE Trans. on Aerospace and Electronic Systems, vol. 37, no. 1, pp. 292–296, Jan. 2001.

    Article  Google Scholar 

  14. K. Hu and J. Yuan, “Improved robust H filtering for uncertain discrete-time switched systems,” IET Control Theory & Applications, vol. 3, no. 3, pp. 315–324, Mar. 2009.

    Article  MathSciNet  Google Scholar 

  15. J. Zhang and Q. Xia, “New LMI approach to fuzzy H filter designs,” IEEE Trans. on Circuits and Systems-Π: Express Briefs, vol. 56, no. 9, pp. 739–743, Sep. 2009.

    Article  Google Scholar 

  16. S. Xu, “Robust H filtering for a class of discretetime uncertain nonlinear systems with state delay,” IEEE Trans. on Circuits and Systems I: Fundamental Theory and Applications, vol. 49, no. 12, pp. 1853–1859, Dec. 2002.

    Article  Google Scholar 

  17. X. H. Chang and G. H. Yang, “Robust H filtering for uncertain discrete-time systems using parameter-dependent Lyapunov functions,” Journal of Control Theory and Applications, vol. 11, no. 1, pp. 122–127, Feb. 2013.

    Article  MathSciNet  Google Scholar 

  18. S. Xu and T. Chen, “Robust H control for uncertain discrete-time systems with time-varying delays via exponential output feedback controllers,” Systems & Control Letters, vol. 51, no. 3–4, pp. 171–183, Mar. 2004.

    Article  MathSciNet  MATH  Google Scholar 

  19. I. R. Petersen, “A stabilization algorithm for a class of uncertain linear systems,” Systems & Control Letters, vol. 8, no. 4, pp. 351–357, Mar. 1987.

    Article  MathSciNet  MATH  Google Scholar 

  20. C. E. De. Souza, A. Trofino, and K. A. Barbosa, “Mode-independent H filters for Markovian jump linear systems,” IEEE Trans. on Automatic Control, vol. 51, no. 11, pp. 1837–1841, Nov. 2006.

    Article  Google Scholar 

  21. R. E. Skelton, T. Iwasaki, and K. Grigoriadis, “A unified approach to linear control design,” Taylor and Francis Series in Systems and Control, 1998.

  22. F. Delmotte, T. M. Guerra, and M. Ksantini, “Continuous Takagi-Sugeno’s models: reduction of the number of LMI conditions in various fuzzy control design technics,” IEEE Trans. on Fuzzy Systems, vol. 15, no. 3, pp. 426–438, Jun. 2007.

    Article  Google Scholar 

  23. L. Xie, L. Lu, D. Zhang, and H. Zhang, “Improved robust H 2 and H filtering for uncertain discretetime systems,” Automatica, vol. 40, no. 5, pp. 873–880, May 2004.

    Article  MathSciNet  MATH  Google Scholar 

  24. P. Gahinet, A. Nemirovski, A. J. Laub, and M. Chilali, LMI Control Toolbox, The MathWorks Inc., Natick, 1995.

    Google Scholar 

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Correspondence to Xiao-Heng Chang.

Additional information

The work of Xiao-Heng Chang was supported in part by the Funds of National Science of China (Grant No. 61104071), the Program for Liaoning Excellent Talents in University (Grant No. LJQ2012095).

Recommended by Editorial Board member Shengyuan Xu under the direction of Editor Yoshito Ohta.

Ke-Zhen Han received his B.E. degree from Dezhou University, China in 2010. He is currently working toward an M.S. degree in the College of Engineering, Bohai University, China. His research interests include robust control, singular system theory and fuzzy control.

Xiao-Heng Chang received his B.E. and M.S. degrees from the Liaoning Technical University, China, in 1998 and 2004, respectively, and his Ph.D. degree from the Northeastern University, China, in 2007. He is currently an Associate professor in the College of Engineering, Bohai University, China. His research interests include fuzzy control and robust control as well as their applications.

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Han, KZ., Chang, XH. Parameter-dependent robust H filter design for uncertain discrete-time systems with quantized measurements. Int. J. Control Autom. Syst. 11, 194–199 (2013). https://doi.org/10.1007/s12555-012-0040-2

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  • DOI: https://doi.org/10.1007/s12555-012-0040-2

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