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Reliable filtering for fuzzy Markov stochastic systems with sensor failures and packet dropouts

Reliable filtering for fuzzy Markov stochastic systems with sensor failures and packet dropouts

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This study addresses the filter design issue for fuzzy Markov stochastic systems with sensor failures and packet dropouts. A more general failure model is used for Markov systems to better describe the sensor failures, and the packet dropouts are assumed to obey a series of Bernoulli processes which are formed into a diagonal matrix. Sufficient condition is established to guarantee that the filtering error system is stochastically stable and achieves the given performance. The parameters of the filter are then derived by solving linear matrix inequalities. Simulation results are given to demonstrate the usefulness and availability of the proposed method.

References

    1. 1)
      • 1. Takagi, T., Sugeno, M.: ‘Fuzzy identification of systems and its applications to modeling and control’, IEEE Trans. Syst. Man Cybern., 1985, SMC-15, pp. 116132.
    2. 2)
      • 2. Li, H., Wu, C., Feng, Z.: ‘Fuzzy dynamic output-feedback control of non-linear networked discrete-time system with missing measurements’, IET Control Theory Appl., 2015, 9, pp. 327335.
    3. 3)
      • 3. Liu, Y., Guo, B., Park, J.: ‘Non-fragile H filtering for delayed Tagaki–Sugeno fuzzy systems with randomly occurring gain variations’, Fuzzy Sets Syst., 2017, 316, pp. 99116.
    4. 4)
      • 4. Li, X., Yang, G.: ‘Fault detection for T–S fuzzy systems with unknown membership functions’, IEEE Trans. Fuzzy Syst., 2014, 22, pp. 139152.
    5. 5)
      • 5. Xu, Y., Lu, R., Peng, H., et al: ‘Filtering for fuzzy systems with multiplicative sensor noises and multi-density quantizer’, IEEE Trans. Fuzzy Syst., doi: 10.1109/TFUZZ.2017.2702119.
    6. 6)
      • 6. Feng, G.: ‘A survey on analysis and design of model-based fuzzy control systems’, IEEE Trans. Fuzzy Syst., 2006, 14, pp. 676697.
    7. 7)
      • 7. Liu, Y., Park, J., Guo, B.: ‘Non-fragile H filtering for nonlinear discrete-time delay systems with randomly occurring gain variations’, ISA Trans., 2016, 63, pp. 196203.
    8. 8)
      • 8. Chang, X., Xiong, J., Park, J.: ‘Resilient H filtering for discrete-time systems’, Signal Processing, 2016, 127, pp. 7179.
    9. 9)
      • 9. Gao, H., Wang, C.: ‘Delay-dependent robust H and L2L filtering for a class of uncertain nonlinear time-delay systems’, IEEE Trans. Autom. Control, 2003, 48, pp. 16611666.
    10. 10)
      • 10. Li, X., Yang, G.: ‘Finite frequency L2L filtering of T–S fuzzy systems with unknown membership functions’, IEEE Trans. Syst. Man Cybern. Syst., doi: 10.1109/TSMC.2016.2563390.
    11. 11)
      • 11. Zhang, H., Shi, Y., Wang, J.: ‘On energy-to-peak filtering for nonuniformly sampled nonlinear systems: a Markovian jump system approach’, IEEE Trans. Fuzzy Syst., 2014, 22, pp. 212222.
    12. 12)
      • 12. Costa, O., Fragoso, M., Marques, R.: ‘Discrete-time Markovian jump linear systems’ (Springer, London, 2005).
    13. 13)
      • 13. Zhang, L., Boukas, E.: ‘Mode-dependent H filtering for discrete-time Markovian jump linear systems with partly unknown transition probabilities’, Automatica, 2009, 45, pp. 14621467.
    14. 14)
      • 14. Luan, X., Shi, P., Liu, F.: ‘Finite-time stabilisation for Markov jump systems with Gaussian transition probabilities’, IET Control Theory Appl., 2013, 7, pp. 298304.
    15. 15)
      • 15. Shen, M., Ye, D., Fei, S.: ‘Robust H static output control of discrete Markov jump linear systems with norm bounded uncertainties’, IET Control Theory Appl., 2014, 8, pp. 14491455.
    16. 16)
      • 16. Shen, M., Park, J.: ‘H Filtering of Markov jump linear systems with general transition probabilities and output quantization’, ISA Trans., 2016, 63, pp. 204210.
    17. 17)
      • 17. Shen, H., Wu, Z., Park, J.: ‘Reliable mixed passive and H filtering for semi-Markov jump systems with randomly occurring uncertainties and sensor failures’, Int. J. Robust Nonlinear Control, 2015, 25, pp. 32313251.
    18. 18)
      • 18. Shi, Y., Yu, B.: ‘Output feedback stabilization of networked control systems with random delays modeled by Markov chains’, IEEE Trans. Autom. Control, 2009, 54, pp. 16681674.
    19. 19)
      • 19. Xu, Y., Lu, R., Peng, H., et al: ‘Asynchronous dissipative state estimation for stochastic complex networks with quantized jumping coupling and uncertain measurements’, IEEE Trans. Neural Netw. Learn. Syst., 2017, 28, pp. 268277.
    20. 20)
      • 20. Wu, H., Cai, K.: ‘Mode-independent robust stabilization for uncertain Markovian jump nonlinear systems via fuzzy control’, IEEE Trans. Syst. Man Cybern. B, Cybern., 2006, 36, pp. 509519.
    21. 21)
      • 21. Li, H., Chen, B., Zhou, Q., et al: ‘Robust stability for uncertain delayed fuzzy Hopfield neural networks with Markovian jumping parameters’, IEEE Trans. Syst. Man Cybern. B, Cybern., 2009, 39, pp. 94102.
    22. 22)
      • 22. Zhang, Y., Xu, S., Zhang, B.: ‘Robust output feedback stabilization for uncertain discrete-time fuzzy Markovian jump systems with time-varying delays’, IEEE Trans. Fuzzy Syst., 2009, 17, pp. 411420.
    23. 23)
      • 23. Zhang, L., Ning, Z., Shi, P.: ‘Input–output approach to control for fuzzy Markov jump systems with time-varying delays and uncertain packet dropout rate’, IEEE Trans. Syst. Man Cybern., 2015, 45, pp. 24492460.
    24. 24)
      • 24. Hespanaha, J., Naghshtabrizi, P., Xu, Y.: ‘A survey of recent results in networked control systems’, Proc. IEEE, 2007, 95, pp. 138162.
    25. 25)
      • 25. Lu, R., Xu, Y., Xue, A., et al: ‘Networked control with state reset and quantized measurements: observer-based case’, IEEE Trans. Ind. Electron., 2013, 60, pp. 52065213.
    26. 26)
      • 26. Sinopoli, B., Schenato, L., Franceschetti, M., et al: ‘Kalman filtering with intermittent observations’, IEEE Trans. Autom. Control, 2004, 49, pp. 14531464.
    27. 27)
      • 27. You, K., Fu, M., Xie, L.: ‘Mean square stability for Kalman filtering with Markovian packet losses’, Automatica, 2011, 47, pp. 26472657.
    28. 28)
      • 28. Wang, Z., Dong, H., Shen, B., et al: ‘Finite-horizon H filtering with missing measurements and quantization effects’, IEEE Trans. Autom. Control, 2013, 58, pp. 17071718.
    29. 29)
      • 29. Wu, Z., Shi, P., Su, H., et al: ‘Reliable H control for discrete-time fuzzy systems with infinite-distributed delay’, IEEE Trans. Fuzzy Syst., 2012, 20, pp. 2231.
    30. 30)
      • 30. Wu, H., Zhang, H.: ‘Reliable H fuzzy control for continuous-time nonlinear systems with actuator failures’, IEEE Trans. Fuzzy Syst., 2006, 14, pp. 609618.
    31. 31)
      • 31. Wang, Z., Wei, G., Feng, G.: ‘Reliable H control for discrete-time piecewise linear systems with infinite distributed delays’, Automatica, 2009, 45, pp. 29912994.
    32. 32)
      • 32. Yang, G., Ye, D.: ‘Adaptive reliable H filtering against sensor failures’, IEEE Trans. Signal Process., 2007, 55, pp. 31613171.
    33. 33)
      • 33. Li, X., Yang, G.: ‘Robust adaptive fault-tolerant control for uncertain linear systems with actuator failures’, IET Control Theory Appl., 2012, 6, pp. 15441551.
    34. 34)
      • 34. Jin, X., He, Y., He, Y.: ‘Finite-time robust fault-tolerant control against actuator faults and saturations’, IET Control Theory Appl., 2017, 11, pp. 550556.
    35. 35)
      • 35. Zhai, D., An, L., Ye, D., et al: ‘Adaptive reliable H static output feedback control against Markovian jumping sensor failures’, IEEE Trans. Neural Netw. Learn. Syst., doi: 10.1109/TNNLS.2016.2639290.
    36. 36)
      • 36. Bai, J., Fu, M., Su, H.: ‘Delay modeling and estimation of a wireless based network control system’, Asian Control Conf., 2011, pp. 187192.
    37. 37)
      • 37. Xie, L.: ‘Output feedback H control of systems with parameter uncertainty’, Int. J. Control, 1996, 63, pp. 741750.
    38. 38)
      • 38. Tao, J., Lu, R., Shi, P., et al: ‘Dissipativity-based reliable control for fuzzy Markov jump systems with actuator faults’, IEEE Trans. Fuzzy Syst., doi: 10.1109/TCYB.2016.2584087.
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