Skip to main content
Log in

Interval Type-2 Fuzzy Passive Filtering for Nonlinear Singularly Perturbed PDT-Switched Systems and Its Application

  • Published:
Journal of Systems Science and Complexity Aims and scope Submit manuscript

Abstract

The problem of designing a passive filter for nonlinear switched singularly perturbed systems with parameter uncertainties is explored in this paper. Firstly, the multiple-time-scale phenomenon is settled effectively by introducing a singular perturbation parameter in the plant. Secondly, the interval type-2 fuzzy set theory is employed where parameter uncertainties are expressed in membership functions rather than the system matrices. It is worth noting that interval type-2 fuzzy sets of the devised filter are different from the plant, which makes the design of the filter more flexible. Thirdly, the persistent dwell-time switching rule, as a kind of time-dependent switching rules, is used to manage the switchings among nonlinear singularly perturbed subsystems, and this rule is more general than dwell-time and average dwell-time switching rules. Next, sufficient conditions are provided for guaranteeing that the filtering error system is globally uniformly exponentially stable with a passive performance. Furthermore, on the basis of the linear matrix inequalities, the explicit expression of the designed filter can be obtained. Finally, a tunnel diode electronic circuit is rendered as an example to confirm the correctness and the validity of the developed filter.

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.

Institutional subscriptions

Similar content being viewed by others

References

  1. Zong G D and Zhao H J, Input-to-state stability of switched nonlinear delay systems based on a novel Lyapunov-Krasovskii functional method, Journal of Systems Science and Complexity, 2018, 31(4): 875–888.

    MathSciNet  MATH  Google Scholar 

  2. Wang Z, Shen L, Xia J W, et al., Finite-time non-fragile l2-l control for jumping stochastic systems subject to input constraints via an event-triggered mechanism, J. Franklin Inst., 2018, 355(14): 6371–6389.

    MathSciNet  MATH  Google Scholar 

  3. Shen L, Yang X F, Wang J, et al., Passive gain-scheduling filtering for jumping linear parameter varying systems with fading channels based on the hidden Markov model, Proc.Inst. Mech.Eng. Part I–J Syst. Control Eng., 2019, 233(1): 67–79.

    Google Scholar 

  4. Wang J, Huo S C, Xia J W, et al., Generalised dissipative asynchronous output feedback control for Markov jump repeated scalar non-linear systems with time-varying delay, IET Control Theory Appl., 2019, 13(13): 2114–2121.

    Google Scholar 

  5. Li J, Pan K P, Zhang D Z, et al., Robust fault detection and estimation observer design for switched systems, Nonlinear Anal. Hybrid. Syst., 2019, 34: 30–42.

    MathSciNet  MATH  Google Scholar 

  6. Shen H, Men Y Z, Cao J D, et al., H filtering for fuzzy jumping genetic regulatory networks with round-robin protocol: A hidden-Markov-model-based approach, IEEE Trans. Fuzzy Syst., 2020, 28(1): 112–121.

    Google Scholar 

  7. Su Q Y, Fan Z X, Lu T, et al., Fault detection for switched systems with all modes unstable based on interval observer, Inf. Sci., 2020, 517: 167–182.

    MathSciNet  MATH  Google Scholar 

  8. Wang X L, Xia J W, Wang J, et al., Reachable set estimation for Markov jump LPV systems with time delays, Appl. Math. Comput., 2020, 376: 125117.

    MathSciNet  MATH  Google Scholar 

  9. Hu X H, Xia J W, Wang Z, et al., Robust distributed state estimation for Markov coupled neural networks under imperfect measurements, J. Franklin Inst., 2020, 357(4): 2420–2436.

    MathSciNet  MATH  Google Scholar 

  10. Van Der Schaft A J and Schumacher J M, An Introduction to Hybrid Dynamical Systems, Springer, London, 2000.

    MATH  Google Scholar 

  11. Wang Y D, Xia J W, Wang Z, et al., Design of a fault-tolerant output-feedback controller for thickness control in cold rolling mills, Appl. Math. Comput., 2020, 369: 124841.

    MathSciNet  MATH  Google Scholar 

  12. Shen H, Huo S C, Yan H C, et al., Distributed dissipative state estimation for Markov jump genetic regulatory networks subject to round-robin scheduling, IEEE Trans. Neural Netw. Learn. Syst., 2020, 31(3): 762–771.

    MathSciNet  Google Scholar 

  13. Xing M P, Xia J W, Wang J, et al., Asynchronous H filtering for nonlinear persistent dwell-time switched singular systems with measurement quantization, Appl. Math. Comput., 2019, 362: 124578.

    MathSciNet  MATH  Google Scholar 

  14. Cheng J, Park J H, Cao J D, et al., Hidden Markov model-based nonfragile state estimation of switched neural network with probabilistic quantized outputs, IEEE Trans. Cybern., 2020, 50(5): 1900–1909.

    Google Scholar 

  15. Shen H, Xing M P, Wu Z G, et al., Multiobjective fault-tolerant control for fuzzy switched systems with persistent dwell time and its application in electric circuits, IEEE Trans. Fuzzy Syst., 2020, 28(10): 2335–2347.

    Google Scholar 

  16. Hespanha J P and Morse A S, Stability of switched systems with average dwell-time, Proceedings of the 38th IEEE Conference on Decision and Control, Phoenix, AZ, USA, 1999.

  17. Lin X Z, Li X L, and Park J H, Output-feedback stabilization for planar output-constrained switched nonlinear systems, Int. J. Robust & Nonlinear Control, 2020, 30(5): 1819–1830.

    MathSciNet  MATH  Google Scholar 

  18. Lin X Z, Zhang W L, Yang Z L, et al., Finite-time boundedness of switched systems with time-varying delays via sampled-data control, Int. J. Robust & Nonlinear Control, 2020, 30(7): 2953–2976.

    MathSciNet  MATH  Google Scholar 

  19. Shen H, Huang Z G, Cao J D, et al., Exponential \({{\cal H}_\infty }\) filtering for continuous-time switched neural networks under persistent dwell-time switching regularity, IEEE Trans. Cybern., 2020, 50(6): 2440–2449.

    Google Scholar 

  20. Shen H, Xing M P, Yan H C, et al., Extended dissipative filtering for persistent dwell-time switched systems with packet dropouts, IEEE Trans. Syst. Man Cybern. Syst., 2020, 50(11): 4796–4806.

    Google Scholar 

  21. Cheng J, Zhang D, Qi W H, et al., Finite-time stabilization of T-S fuzzy semi-Markov switching systems: A coupling memory sampled-data control approach, J. Franklin Inst., 2020, 357(16): 11265–11280.

    MathSciNet  MATH  Google Scholar 

  22. Hespanha J P, Uniform stability of switched linear systems: Extensions of LaSalle’s invariance principle, IEEE Trans. Autom. Control, 2004, 49(4): 470–482.

    MathSciNet  MATH  Google Scholar 

  23. Xing M P, Xia J W, Huang X, et al., On dissipativity-based filtering for discrete-time switched singular systems with sensor failures: A persistent dwell-time scheme, IET Control Theory Appl., 2019, 13(12): 1814–1822.

    MathSciNet  MATH  Google Scholar 

  24. Wang J, Yang C Y, Shen H, et al., Sliding-mode control for slow-sampling singularly perturbed systems subject to Markov jump parameters, IEEE Trans. Syst. Man Cybern. Syst., 2020, DOI: https://doi.org/10.1109/TSMC.2020.2979860.

  25. Fang L D, Ma L, Ding S H, et al., Finite-time stabilization for a class of high-order stochastic nonlinear systems with an output constraint, Appl. Math. Comput., 2019, 358(1): 63–79.

    MathSciNet  MATH  Google Scholar 

  26. Ding S H, Chen W H, Mei K Q, et al., Disturbance observer design for nonlinear systems represented by input-output models, IEEE Trans. Industrial Elec., 2020, 67(2): 1222–1232.

    Google Scholar 

  27. Wu T Y, Huang X, Chen X Y, et al., Sampled-data \({{\cal H}_\infty }\) exponential synchronization for delayed semi-Markov jump CDNs: A looped-functional approach, Appl. Math. Comput., 2020, 377: 125156.

    MathSciNet  MATH  Google Scholar 

  28. Jin X Z, Zhao X F, Yu J G, et al., Adaptive fault-tolerant consensus for a class of leader-following systems using neural network learning strategy, Neural Netw., 2020, 121: 474–483.

    MATH  Google Scholar 

  29. Jin X Z, Che W W, Wu Z G, et al., Adaptive consensus and circuital implementation of a class of faulty multiagent systems, IEEE Trans. Syst. Man Cybern. Syst., 2020, DOI: https://doi.org/10.1109/TSMC.2020.2995802.

  30. Liang H J, Guo X Y, Pan Y N, et al., Event-triggered fuzzy bipartite tracking control for network systems based on distributed reduced-order observers, IEEE Trans. Fuzzy Syst., 2020, DOI: https://doi.org/10.1109/TFUZZ.2020.2982618.

  31. Liang H J, Liu G L, Zhang H G, et al., Neural-network-based event-triggered adaptive control of nonaffine nonlinear multi-agent systems with dynamic uncertainties, IEEE Trans. Neural Netw. Learn. Syst., 2020, DOI: https://doi.org/10.1109/TNNLS.2020.3003950.

  32. Dong J X and Yang G H, \({{\cal H}_\infty }\) control for fast sampling discrete-time singularly perturbed systems, Automatica, 2008, 44(5): 1385–1393.

    MathSciNet  MATH  Google Scholar 

  33. Shen H, Li F, Wu Z G, et al., Fuzzy-model-based nonfragile control for nonlinear singularly perturbed systems with semi-Markov jump parameters, IEEE Trans. Fuzzy Syst., 2018, 26(6): 3428–3439.

    Google Scholar 

  34. Pan Y N and Yang G H, Event-triggered fault detection filter design for nonlinear networked systems, IEEE Trans. Syst. Man Cybern. Syst., 2018, 48(11): 1851–1862.

    Google Scholar 

  35. Li X H, Lu D K, Zhang W, et al., Sensor fault estimation and fault-tolerant control for a class of Takagi-Sugeno Markovian jump systems with partially unknown transition rates based on the reduced-order observer, Journal of Systems Science and Complexity, 2018, 31(6): 1405–1422.

    MathSciNet  MATH  Google Scholar 

  36. Ru T T, Xia J W, Huang X, et al., Reachable set estimation of delayed fuzzy inertial neural networks with Markov jumping parameters, J. Franklin Inst., 2020, 357(11): 6882–6898.

    MathSciNet  MATH  Google Scholar 

  37. Zhao T and Dian S Y, Fuzzy static output feedback H control for nonlinear systems subject to parameter uncertainties, Journal of Systems Science and Complexity, 2018, 31(2): 343–371.

    MathSciNet  MATH  Google Scholar 

  38. Lam H K and Seneviratne L D, Stability analysis of interval type-2 fuzzy-model-based control systems, IEEE Trans. Syst. Man Cybern. Part B, 2008, 38(3): 617–628.

    Google Scholar 

  39. Rong N N and Wang Z S, Fixed-time stabilization for IT2 T-S fuzzy interconnected systems via event-triggered mechanism: An exponential gain method, IEEE Trans. Fuzzy Syst., 2020, 28(2): 246–258.

    Google Scholar 

  40. Pan Y N and Yang G H, Switched filter design for interval type-2 fuzzy systems with sensor nonlinearities, Neurocomputing, 2016, 194: 168–175.

    Google Scholar 

  41. Xue M Q, Tang Y, Wu L G, et al., Switching stabilization for type-2 fuzzy systems with network-induced packet losses, IEEE Trans. Cybern., 2019, 49(7): 2591–2604.

    Google Scholar 

  42. Li H Y, Wu C W, Wu L G, et al., Filtering of interval type-2 fuzzy systems with intermittent measurements, IEEE Trans. Cybern., 2016, 46(3): 668–678.

    Google Scholar 

  43. Li H Y, Yin S, Pan Y N, et al., Model reduction for interval type-2 Takagi-Sugeno fuzzy systems, Automatica, 2015, 61: 308–314.

    MathSciNet  MATH  Google Scholar 

  44. Zhang L X, Zhu Y Z, Shi P, et al., Time-Dependent Switched Discrete-Time Linear Systems: Control and Filtering, Springer, New York, 2016.

    MATH  Google Scholar 

  45. Lam H K, Li H Y, Deters C, et al., Control design for interval type-2 fuzzy systems under imperfect premise matching, IEEE Trans. Industrial Elec., 2014, 61(2): 956–968.

    Google Scholar 

  46. Wang X L, Xia J W, Wang J, et al., Passive state estimation for fuzzy jumping neural networks with fading channels based on the hidden Markov model, Phys. A, 2019, 535: 122437.

    MathSciNet  Google Scholar 

  47. Wan X B, Wang Z D, Wu M, et al., H state estimation for discrete-time nonlinear singularly perturbed complex networks under the round-robin protocol, IEEE Trans. Neural Netw. Learn. Syst., 2019, 30(2): 415–426.

    MathSciNet  Google Scholar 

  48. Li H Y, Wu L G, Lam H K, et al., Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems, Springer, Singapore, 2016.

    MATH  Google Scholar 

  49. Boyd S, Ghaoui L E, Feron E, et al., Linear Matrix Inequalities in System and Control Theory, SIAM, Philadelphia, 1994.

    MATH  Google Scholar 

  50. Assawinchaichote W, Nguang S K, and Shi P, Fuzzy control and Filter Design for Uncertain Fuzzy Systems, Springer, Berlin, 2006.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hao Shen.

Additional information

This research was supported by the National Natural Science Foundation of China under under Grant Nos. 61873002, 61703004, 61973199, the Natural Science Foundation of Anhui Province under Grant No. 1808085QA18.

This paper was recommended for publication by Editor LI Hongyi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, X., Xia, J., Wang, J. et al. Interval Type-2 Fuzzy Passive Filtering for Nonlinear Singularly Perturbed PDT-Switched Systems and Its Application. J Syst Sci Complex 34, 2195–2218 (2021). https://doi.org/10.1007/s11424-020-0106-9

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11424-020-0106-9

Keywords

Navigation