Skip to main content
Log in

Dynamic event-triggered non-fragile dissipative filtering for interval type-2 fuzzy Markov jump systems

  • Original Article
  • Published:
International Journal of Machine Learning and Cybernetics Aims and scope Submit manuscript

Abstract

This paper studies the design of non-fragile dissipative filters for discrete-time interval type-2 fuzzy Markov jump systems (IT-2FMJSs). The novel mode-dependent dynamic event-triggered strategy (DETS) is used to lower the frequency of filter updates while improving information transmission efficiency. In addition, the hidden Markov model is employed to construct an asynchronous, non-fragile dissipative filter of uncertain interval type. The mode-independent and dependent filters can be effectively coupled by modifying the conditional probability matrices (CPMs) and the interval value range of uncertain terms. Furthermore, the vertex separation approach is used to address the computational difficulty of interval uncertainty in the filter. Finally, sufficient requirements are obtained based on the Lyapunov stability theory to guarantee that the filtering error system is stochastically stable with extended dissipative performance. The correctness and effectiveness of the proposed conclusions are illustrated by two simulation examples.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Data availability

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Wang J, Yang C, Xia J, Wu Z-G, Shen H (2022) Observer-based sliding mode control for networked fuzzy singularly perturbed systems under weighted try-once-discard protocol. IEEE Trans Fuzzy Syst 30(6):1889–1899

    Article  Google Scholar 

  2. Wang L, Zhao Y, Xie X, Lam H-K (2023) A switching asynchronous control approach for Takagi-Sugeno fuzzy Markov jump systems with time-varying delay. IEEE Trans Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2023.3302134

    Article  Google Scholar 

  3. Visakamoorthi B, Palanisamy M, Trinh H (2022) Reachable set estimation for T-S fuzzy Markov jump systems with time-varying delays via membership function dependent \(H_{\infty }\) performance. IEEE Trans Fuzzy Syst 30:4980–4990

    Article  Google Scholar 

  4. Liu J, Ran G, Huang Y, Han C, Yu Y, Sun C (2022) Adaptive event-triggered finite-time dissipative filtering for interval type-2 fuzzy Markov jump systems with asynchronous modes. IEEE Trans Cybern 52:9709–9721

    Article  Google Scholar 

  5. Zhang X, Wang H, Stojanovic V, Cheng P, He S, Luan X, Liu F (2022) Asynchronous fault detection for interval type-2 fuzzy nonhomogeneous higher-level Markov jump systems with uncertain transition probabilities. IEEE Trans Fuzzy Syst 30:2487–2499

    Article  Google Scholar 

  6. Han Y, Zhou S (2021) Extended dissipative filtering for Markovian jump interval-valued fuzzy systems with uncertain transition rates. Fuzzy Sets Syst 416:86–107

    Article  MathSciNet  Google Scholar 

  7. Lu Z, Ran G, Xu F, Lu J (2019) Novel mixed-triggered filter design for interval type-2 fuzzy nonlinear Markovian jump systems with randomly occurring packet dropouts. Nonlinear Dyn 97(2):1525–1540

    Article  Google Scholar 

  8. Papadopoulos CT, Li J, O’Kelly ME (2019) A classification and review of timed Markov models of manufacturing systems. Comput Ind Eng 128:219–244

    Article  Google Scholar 

  9. Wang J, Xia J, Shen H, Xing M, Park JH (2021) \(\cal{H} _{\infty }\) synchronization for fuzzy Markov jump chaotic systems with piecewise-constant transition probabilities subject to PDT switching rule. IEEE Trans Fuzzy Syst 29(10):3082–3092

    Article  Google Scholar 

  10. Qi W, Zong G, Karimi HR (2018) \(\mathscr {L}\) control for positive delay systems with semi-Markov process and application to a communication network model. IEEE Trans Ind Electron 66(3):2081–2091

    Article  Google Scholar 

  11. Qi W, Zong G, Hou Y, Chadli M (2023) SMC for discrete-time nonlinear semi-Markovian switching systems with partly unknown semi-Markov Kernel. IEEE Trans Autom Control 68(3):1855–1861

    Article  MathSciNet  Google Scholar 

  12. Tian Y, Wang Z (2021) A switched fuzzy filter approach to \(H_{\infty }\) filtering for Takagi-Sugeno fuzzy Markov jump systems with time delay: the continuous-time case. Inf Sci 557:236–249

    Article  MathSciNet  Google Scholar 

  13. Xiong J, Lam J (2006) Fixed-order robust \(H_{\infty }\) filter design for Markovian jump systems with uncertain switching probabilities. IEEE Trans Signal Process 54(4):1421–1430

    Google Scholar 

  14. Hua M, Zhang L, Yao F, Ni J, Dai W, Cheng Y (2018) Robust \(H_{\infty }\) filtering for continuous-time nonhomogeneous Markov jump nonlinear systems with randomly occurring uncertainties. Signal Process 148:250–259

    Article  Google Scholar 

  15. Wu ZG, Shi P, Su H, Chu J (2014) Asynchronous \(l_2\) - \(l_{\infty }\) filtering for discrete-time stochastic Markov jump systems with randomly occurred sensor nonlinearities. Automatica 50(1):180–186

    Article  MathSciNet  Google Scholar 

  16. Shen H, Wang T, Cao J, Lu G, Song Y, Huang T (2018) Nonfragile dissipative synchronization for Markovian memristive neural networks: a gain-scheduled control scheme. IEEE Trans Neural Netw Learn Systems 30(6):1841–1853

    Article  MathSciNet  Google Scholar 

  17. Liu X, Xia J, Wang J, Shen H (2021) Interval type-2 fuzzy passive filtering for nonlinear singularly perturbed PDT-switched systems and its application. J Syst Sci Complex 34:2195–2218

    Article  MathSciNet  Google Scholar 

  18. Song Q, Chen S, Zhao Z, Liu Y, Alsaadi FE (2021) Passive filter design for fractional-order quaternion-valued neural networks with neutral delays and external disturbance. Neural Netw 137:18–30

    Article  Google Scholar 

  19. Li L, Yang R, Feng Z, Wu L (2022) Dissipative filtering for two-dimensional LPV systems: a hidden Markov model approach. ISA Trans 130:409–419

    Article  Google Scholar 

  20. Li Q, Zhu Q, Zhong S, Zhong F (2017) Extended dissipative state estimation for uncertain discrete-time Markov jump neural networks with mixed time delays. Isa Trans 66:200–208

    Article  Google Scholar 

  21. Yang G-H, Che W-W (2008) Non-fragile \(H_{\infty }\) filter design for linear continuous-time systems. Automatica 44(11):2849–2856

    Article  MathSciNet  Google Scholar 

  22. Shen M, Park JH, Fei S (2018) Event-triggered nonfragile \(H_{\infty }\) filtering of Markov jump systems with imperfect transmissions. Signal Process 149:204–213

    Article  Google Scholar 

  23. Ma Y, Yan H (2013) Delay-dependent non-fragile robust dissipative filtering for uncertain nonlinear stochastic singular time-delay systems with Markovian jump parameters. Adv Differ Equ 1:1–20

    MathSciNet  Google Scholar 

  24. Nithya V, Sakthivel R, Alzahrani F (2020) Dissipative-based non-fragile filtering for fuzzy networked control systems with switching communication channels. Appl Math Comput 373:125011

    MathSciNet  Google Scholar 

  25. Fan S, Yan H, Zhang H, Shen H, Shi K (2020) Dynamic event-based non-fragile dissipative state estimation for quantized complex networks with fading measurements and its application. IEEE Trans Circ Syst I Reg Pap 68(2):856–867

    Article  MathSciNet  Google Scholar 

  26. Zhang D, Shi P, Wang QG, Yu L (2017) Distributed non-fragile filtering for T-S fuzzy systems with event-based communications. Fuzzy Sets Syst 306:137–152

    Article  MathSciNet  Google Scholar 

  27. Wang H, Ying Y, Xue A (2021) Event-triggered \(H_{\infty }\) filtering for discrete-time Markov jump systems with repeated scalar nonlinearities. Circ Syst Signal Process 40(2):669–690

    Article  Google Scholar 

  28. Yuan M, Chadli M, Wang Z-P, Zhao D, Li Y (2023) Event-triggered non-fragile state estimator design for interval type-2 TakagiC̈Sugeno fuzzy systems with bounded disturbances. Nonlinear Anal Hybrid Syst 49:101376

    Article  Google Scholar 

  29. Qi W, Zhang N, Zong G, Su S-F, Yan H, Yeh R-H (2023) Event-triggered SMC for networked Markov jumping systems with channel fading and applications: genetic algorithm. IEEE Trans Cybern 53(10):6503–6515

    Article  Google Scholar 

  30. Yao D, Zhang B, Li P, Li H (2018) Event-triggered sliding mode control of discrete-time Markov jump systems. IEEE Trans Syst Man Cybern Syst 49(10):2016–2025

    Article  Google Scholar 

  31. Wang H, Zhang D, Lu R (2018) Event-triggered \(H_{\infty }\) filter design for Markovian jump systems with quantization. Nonlinear Anal Hybrid Syst 28:23–41

    Article  MathSciNet  Google Scholar 

  32. Rakkiyappan R, Maheswari K, Velmurugan G, Park JH (2018) Event-triggered \(H_{\infty }\) state estimation for semi-Markov jumping discrete-time neural networks with quantization. Neural Netw 105:236–248

    Article  Google Scholar 

  33. Ji Y, Wu W, Fu H, Qiao H (2021) Passivity-based filtering for networked semi-Markov robotic manipulators with mode-dependent quantization and event-triggered communication. Int J Adv Robot Syst 18:1–9

    Article  Google Scholar 

  34. Zhou X, Cheng J, Cao J, Park JH (2022) Event-based asynchronous dissipative filtering for fuzzy nonhomogeneous Markov switching systems with variable packet dropouts. Fuzzy Sets Syst 432:50–67

    Article  MathSciNet  Google Scholar 

  35. Wang Y, Zhuang G, Chen F (2020) A dynamic event-triggered \(H_{\infty }\) control for singular Markov jump systems with redundant channels. Int J Syst Sci 51(1):158–179

    Article  MathSciNet  Google Scholar 

  36. Liang R, Xiao Z, Wu Z, Tao J, Wang X (2022) Dynamic event-triggered and asynchronous sliding mode control for T-S fuzzy Markov jump systems. Nonlinear Dyn 1–14

  37. Zhang Z, Su SF, Niu Y (2020) Dynamic event-triggered control for interval type-2 fuzzy systems under fading channel. IEEE Trans Cybern 51(11):5342–5351

    Article  Google Scholar 

  38. Wang Y, Chen F, Zhuang G (2020) Dynamic event-based reliable dissipative asynchronous control for stochastic Markov jump systems with general conditional probabilities. Nonlinear Dyn 101(1):465–485

    Article  Google Scholar 

  39. Wang J, Shen L, Xia J, Wang Z, Chen X (2020) Asynchronous dissipative filtering for nonlinear jumping systems subject to fading channels. J Frankl Inst 357(1):589–605

    Article  MathSciNet  Google Scholar 

  40. Dai M, Xia J, Park JH, Huang X, Shen H (2019) Asynchronous dissipative filtering for Markov jump discrete-time systems subject to randomly occurring distributed delays. J Frankl Inst 356(4):2395–2420

    Article  MathSciNet  Google Scholar 

  41. Zhang Y, Chen X, Wang J, Shi K, Shen H (2022) Generalized dissipative state estimation for discrete-time nonhomogeneous semi-Markov jump nonlinear systems. J Frankl Inst 359(4):1689–1705

    Article  MathSciNet  Google Scholar 

  42. Xia Y, Xia J, Wang Z, Shen H (2020) Extended non-fragile dissipative estimation for nonlinear semi-Markov jump systems. J Frankl Inst 357(1):457–472

    Article  MathSciNet  Google Scholar 

  43. Gong C, Zhu G, Shi P, Agarwal RK (2022) Asynchronous distributed finite-time \(H_{\infty }\) filtering in sensor networks with hidden Markovian switching and two-channel stochastic attacks. IEEE Trans Cybern 52:1502–1514

    Article  Google Scholar 

  44. Tian Y, Wang Z (2021) Asynchronous extended dissipative filtering for T-S fuzzy Markov jump systems. IEEE Trans Syst Man Cybern Syst 52(6):3915–3925

    Article  MathSciNet  Google Scholar 

  45. Qi W, Zhang N, Zong G, Su S-F, Cao J, Cheng J (2023) Asynchronous sliding-mode control for discrete-time networked hidden stochastic jump systems with cyber attacks. IEEE Trans Cybern. https://doi.org/10.1109/TCYB.2023.3300120

    Article  Google Scholar 

  46. Zhu Y, Zhong Z, Zheng WX, Zhou D (2017) HMM-based \(H_{\infty }\) filtering for discrete-time Markov jump LPV systems over unreliable communication channels. IEEE Trans Syst Man Cybern Syst 48(12):2035–2046

    Article  Google Scholar 

  47. Ge X, Han QL, Wang Z (2017) A dynamic event-triggered transmission scheme for distributed set-membership estimation over wireless sensor networks. IEEE Trans Cybern 49(1):171–183

    Article  Google Scholar 

  48. Sakthivel R, Sathishkumar M, Mathiyalagan K, Marshal Anthoni S (2017) Robust reliable dissipative filtering for Markovian jump nonlinear systems with uncertainties. Int J Adapt Control Signal Process 31(1):39–53

    Article  MathSciNet  Google Scholar 

  49. Zhang C-K, He Y, Jiang L, Wu M (2016) An improved summation inequality to discrete-time systems with time-varying delay. Automatica 74:10–15

    Article  MathSciNet  Google Scholar 

  50. Ding D-W, Li X, Shi Z, Guo X (2012) Nonfragile \(H_{\infty }\) filtering for discrete-time TS fuzzy systems. In: Proceedings of the 31st Chinese control conference, IEEE, 2012, pp 3552–3557

  51. Wu ZG, Dong S, Shi P, Su H, Huang T (2017) Reliable filtering of nonlinear Markovian jump systems: the continuous-time case. IEEE Trans Syst Man Cybern Syst 49(2):386–394

    Article  Google Scholar 

  52. Wang J, Li F, Sun Y, Shen H (2016) On asynchronous filtering for networked fuzzy systems with Markov jump parameters over a finite-time interval. IET Control Theory Appl 10(17):2175–2185

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China no. 61273004, and the Natural Science Foundation of Hebei province no. F2021203061.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yuechao Ma.

Ethics declarations

Conflict of interest

In this paper, the authors declare that they have no known competing Conflict of interest in this paper and we declare that we do not have economic conflicts or commercial interests related to the submitted works.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This work is supported by National Natural Science Foundation of China (No. 61273004) and the Natural Science Foundation of Hebei province (No. F2021203061).

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Han, L., Wang, Y. & Ma, Y. Dynamic event-triggered non-fragile dissipative filtering for interval type-2 fuzzy Markov jump systems. Int. J. Mach. Learn. & Cyber. (2024). https://doi.org/10.1007/s13042-024-02204-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s13042-024-02204-5

Keywords

Navigation