Event-based multi-objective filtering for multi-rate time-varying systems with random sensor saturation

Hui Li; Ming Lyu; Baozhu Du

Kybernetika (2020)

  • Volume: 56, Issue: 1, page 81-106
  • ISSN: 0023-5954

Abstract

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This paper focuses on the multi-objective filtering of multirate time-varying systems with random sensor saturations, where both the variance-constrained index and the H index are employed to evaluate the filtering performance. According to address issues, the high-frequency period of the internal state of the system is nondestructively converted to the low-frequency period, which determined by the measurement devices. Then the saturated output of multiple sensors is modeled as a sector bounded nonlinearity. At the same time, in order to reduce the communication frequency between sensors and filters, a communication scheduling rule is designed by the utilization of an event-triggered mechanism. By means of random analysis technology, the sufficient conditions are given to guarantee the preset H performance and variance constraint performance indexes of the system, and then the solution of the desired filter is obtained by using linear matrix inequalities. Finally, the validity and effectiveness of the proposed filter scheme are verified by numerical simulation.

How to cite

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Li, Hui, Lyu, Ming, and Du, Baozhu. "Event-based multi-objective filtering for multi-rate time-varying systems with random sensor saturation." Kybernetika 56.1 (2020): 81-106. <http://eudml.org/doc/296948>.

@article{Li2020,
abstract = {This paper focuses on the multi-objective filtering of multirate time-varying systems with random sensor saturations, where both the variance-constrained index and the $H_\infty $ index are employed to evaluate the filtering performance. According to address issues, the high-frequency period of the internal state of the system is nondestructively converted to the low-frequency period, which determined by the measurement devices. Then the saturated output of multiple sensors is modeled as a sector bounded nonlinearity. At the same time, in order to reduce the communication frequency between sensors and filters, a communication scheduling rule is designed by the utilization of an event-triggered mechanism. By means of random analysis technology, the sufficient conditions are given to guarantee the preset $H_\infty $ performance and variance constraint performance indexes of the system, and then the solution of the desired filter is obtained by using linear matrix inequalities. Finally, the validity and effectiveness of the proposed filter scheme are verified by numerical simulation.},
author = {Li, Hui, Lyu, Ming, Du, Baozhu},
journal = {Kybernetika},
keywords = {multi-rate time-varying system; stochastic saturation; $H_\infty $ filtering; variance-constraints; event-triggered scheme},
language = {eng},
number = {1},
pages = {81-106},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Event-based multi-objective filtering for multi-rate time-varying systems with random sensor saturation},
url = {http://eudml.org/doc/296948},
volume = {56},
year = {2020},
}

TY - JOUR
AU - Li, Hui
AU - Lyu, Ming
AU - Du, Baozhu
TI - Event-based multi-objective filtering for multi-rate time-varying systems with random sensor saturation
JO - Kybernetika
PY - 2020
PB - Institute of Information Theory and Automation AS CR
VL - 56
IS - 1
SP - 81
EP - 106
AB - This paper focuses on the multi-objective filtering of multirate time-varying systems with random sensor saturations, where both the variance-constrained index and the $H_\infty $ index are employed to evaluate the filtering performance. According to address issues, the high-frequency period of the internal state of the system is nondestructively converted to the low-frequency period, which determined by the measurement devices. Then the saturated output of multiple sensors is modeled as a sector bounded nonlinearity. At the same time, in order to reduce the communication frequency between sensors and filters, a communication scheduling rule is designed by the utilization of an event-triggered mechanism. By means of random analysis technology, the sufficient conditions are given to guarantee the preset $H_\infty $ performance and variance constraint performance indexes of the system, and then the solution of the desired filter is obtained by using linear matrix inequalities. Finally, the validity and effectiveness of the proposed filter scheme are verified by numerical simulation.
LA - eng
KW - multi-rate time-varying system; stochastic saturation; $H_\infty $ filtering; variance-constraints; event-triggered scheme
UR - http://eudml.org/doc/296948
ER -

References

top
  1. Chen, W., Ding, D., Ge, X., Han, Q.-L., Wei, G., 10.1109/tcyb.2018.2885567, IEEE Trans. Cybernet. 50 (2020), 4, 1372-1382. DOI10.1109/tcyb.2018.2885567
  2. Chen, W., Ding, D., Dong, H., Wei, G., 10.1109/tsmc.2019.2905253, IEEE Trans. Systems Man Cybernet.: Systems49 (2019), 8, 1688-1697. DOI10.1109/tsmc.2019.2905253
  3. Ding, D., Wang, Z., Han, Q.-L., 10.1109/tac.2019.2934389, IEEE Trans. Automat. Control. 1-11. DOI10.1109/tac.2019.2934389
  4. Ding, D., Wang, Z., Han, Q.-L., Wei, G., 10.1109/tcyb.2018.2827037, IEEE Trans. Cybernet, 49 (2019), 6, 2372-2384. DOI10.1109/tcyb.2018.2827037
  5. Dong, H., Wang, Z., Ho, D., Gao, H., 10.1109/tsp.2010.2042489, IEEE Trans. Signal Process. 58 (2010), 5, 2534-2543. MR2789403DOI10.1109/tsp.2010.2042489
  6. Ge, X., Han, Q.-L., 10.1109/tie.2017.2701778, IEEE Trans. Industr. Electron. 64 (2017), 10, 8118-8127. DOI10.1109/tie.2017.2701778
  7. Ge, X., Han, Q.-L., Wang, Z., 10.1109/tcyb.2017.2789296, IEEE Trans. Cybernet. 49 (2019), 4, 1148-1159. DOI10.1109/tcyb.2017.2789296
  8. Ge, X., Han, Q.-L., Wang, Z., 10.1109/tcyb.2017.2769722, IEEE Trans. Cybernet. 49 (2019), 1, 171-183. DOI10.1109/tcyb.2017.2769722
  9. Hu, C., Qin, W., He, B., Liu, G., 10.14736/kyb-2015-5-0814, Kybernetika 51 (2015), 5, 814-829. MR3445986DOI10.14736/kyb-2015-5-0814
  10. Liang, Y., Chen, T., Pan, Q., 10.1080/00207170902906132, Int. J. Control 82 (2009), 11, 2059-2076. MR2561978DOI10.1080/00207170902906132
  11. Liang, Y., Chen, T., Pan, Q., Multi-rate stochastic H filtering for networked multi-sensor fusion., Kybernetika 46 (2010), 2, 437-444. MR2877091
  12. Liu, S., Wang, Z., Wang, L., Wei, G., 10.1016/j.ins.2018.02.050, Inform. Sci. 459 (2018), 211-223. MR3811013DOI10.1016/j.ins.2018.02.050
  13. Lv, B., Huang, Y., Li, T., Dai, X., He, M., Zhang, W., Yang, Y., 10.4304/jnw.9.12.3445-3453, J. Networks 9 (2014), 12, 3445-53. DOI10.4304/jnw.9.12.3445-3453
  14. Ma, L., Wang, Z., Hu, J., Bo, Y., Guo, Z., 10.1016/j.sigpro.2010.01.010, Signal Process. 90 (2010), 6, 2060-2071. MR2987050DOI10.1016/j.sigpro.2010.01.010
  15. Ma, L., Xu, M., Jia, R., Ye, H., 10.14736/kyb-2014-4-0491, Kybernetika 50 (2014), 4, 491-511. MR3275081DOI10.14736/kyb-2014-4-0491
  16. Shen, B., Tan, H., Wang, Z., Huang, T., 10.1109/tac.2017.2685083, IEEE Trans. Automat. Control 62 (2017), 9, 4753-4759. MR3691900DOI10.1109/tac.2017.2685083
  17. Sinopoli, B., Schenato, L., Franceschetti, M., Poolla, K., Jordan, M., Sastry, S., 10.1109/tac.2004.834121, IEEE Trans. Automat. Control 49 (2004), 9, 1453-1464. MR2086911DOI10.1109/tac.2004.834121
  18. Su, H., Li, Z., Ye, Y., 10.1016/j.isatra.2017.06.019, ISA Trans. 71 (2017), 103-111. MR3468618DOI10.1016/j.isatra.2017.06.019
  19. Subramanian, A., Sayed, A. H., 10.1109/tac.2003.821422, IEEE Trans. Automat. Control 49 (2004), 1, 149-154. MR2028557DOI10.1109/tac.2003.821422
  20. Tan, H., Shen, B., Liu, Y., Alsaedi, A., Ahmad, B., 10.1016/j.inffus.2016.12.003, Inform. Fusion 36 (2017), 313-320. DOI10.1016/j.inffus.2016.12.003
  21. Tian, F., Cui, B., Consensus based minimum variance filter with packet dropouts., Computer Engrg. Appl. 52 (2016), 12, 123-6, 157. 
  22. Wang, Z., Shen, B., Liu, X., 10.1016/j.automatica.2012.01.008, Automatica 48 (2012), 3, 556-562. MR2889455DOI10.1016/j.automatica.2012.01.008
  23. Xiao, Y., Cao, Y., Lin, Z., 10.1109/tsp.2004.826180, IEEE Trans. Signal Process. 52 (2004), 5, 1266-1277. MR2061982DOI10.1109/tsp.2004.826180
  24. Yang, F., Li, Y., 10.1016/j.automatica.2009.04.011, Automatica 45 (2009), 8, 1896-1902. MR2879513DOI10.1016/j.automatica.2009.04.011
  25. Zhang, W., Feng, G., Yu, L., 10.1016/j.automatica.2012.06.027, Automatica 48 (2012), 9, 2016-2028. MR2956878DOI10.1016/j.automatica.2012.06.027
  26. Zhang, X.-M, Han, Q.-L., 10.1109/tcyb.2015.2487420, IEEE Trans. Cybernet. 46 (2016), 12, 2745-2757. DOI10.1109/tcyb.2015.2487420
  27. Zhang, X.-M, Han, Q.-L., Zhang., B., 10.1109/tii.2016.2607150, IEEE Trans. Industr. Inform. 13 (2017), 1, 4-16. DOI10.1109/tii.2016.2607150
  28. Zhang, X.-M, Han, Q.-L., Ge, X., Ding, D., Ding, L., Yue, D., Peng, C., 10.1109/jas.2019.1911651, IEEE/CAA J. Automat. Sinica (2019), 1-17. MR3748030DOI10.1109/jas.2019.1911651
  29. Zhang, Y., Wang, Z., Ma, L., 10.1002/rnc.3520, Int. J. Robust Nonlinear Control 26 (2016), 16, 3507-3523. MR3565746DOI10.1002/rnc.3520
  30. Zhang, Y., Wang, Z., Zou, L., Fang, H., 10.1109/taes.2017.2671498, IEEE Trans. Aerospace Electron. Systems 53 (2017), 3, 1431-1441. DOI10.1109/taes.2017.2671498
  31. Zhong, M., Ye, H., Ding, S., Wang, G., 10.1109/tac.2006.890488, IEEE Trans. Automat. Control 52 (2007), 3, 520-525. MR2300484DOI10.1109/tac.2006.890488
  32. Zou, L., Wang, Z., Hu, J., Gao, H., 10.1109/tac.2017.2691310, IEEE Trans. Automat. Control 62 (2017), 9, 4884-4890. MR3691918DOI10.1109/tac.2017.2691310

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