Skip to main content
SpringerLink
Log in

Reliable Dissipative Interval Type-2 Fuzzy Control for Nonlinear Systems with Stochastic Incomplete Communication Route and Actuator Failure

  • Published:
International Journal of Fuzzy Systems Aims and scope Submit manuscript

Abstract

This paper investigates the dissipative interval type-2 (IT2) fuzzy control issue for a group of uncertain nonlinear systems subject to randomly occurring sensor saturation and quantization. By utilizing the both lower and upper membership functions with relevant tradeoff moduli, uncertainties, which exist in the considered systems, can be captured effectively. During the design of the IT2 fuzzy controller, we take the actuator failure into consideration. Considering the randomicities for the occurrences of sensor saturation and quantization, two separate Bernoulli stochastic distributed courses are utilized to construct the corresponding complicated transmission route. In term of Lyapunov stability theory, sufficient criteria to design dissipative IT2 fuzzy controller are presented to assure the stochastic stability with strict dissipativity of resulting closed-loop systems. Finally, illustrative example verifies the effectiveness and merits of the control strategy proposed in this paper.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Li, Y., Min, X., Tong, S.: Adaptive fuzzy inverse optimal control for uncertain nonlinear systems with full-state constraints. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2935693

    Article  Google Scholar 

  2. Li, Y.: Finite time command filtered adaptive fault tolerant control for a class of uncertain nonlinear systems. Automatica 106, 117–123 (2019)

    Article  MathSciNet  Google Scholar 

  3. Zhai, D., An, L., Dong, J., Zhang, Q.: Switched adaptive fuzzy tracking control for a class of switched nonlinear systems under arbitrary switching. IEEE Trans. Fuzzy Syst. 26(2), 585–597 (2017)

    Article  Google Scholar 

  4. Zhou, Q., Du, P., Li, H., Lu, R., Yang, J.: Adaptive fixed-time control of error-constrained pure-feedback intrconnected nonlinear systems. IEEE Trans. Syst. Man Cybern. Syst. (2019). https://doi.org/10.1109/TSMC.2019.2961371

    Article  Google Scholar 

  5. Zhang, L., Lam, H.K., Sun, Y., Liang, H.: Fault detection for fuzzy semi-Markov jump systems based on interval type-2 fuzzy approach. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2936333

    Article  Google Scholar 

  6. Yang, X., Li, X., Xi, Q., Duan, P.: Review of stability and stabilization for impulsive delayed systems. Math. Biosci. Eng. 15(6), 1495–1515 (2011)

    Article  MathSciNet  Google Scholar 

  7. Li, X., Zhou, Q., Li, P., Li, H., Lu, R.: Event-triggered consensus control for multi-agent systems against false data-injection attacks. IEEE Trans. Cybern. (2019). https://doi.org/10.1109/TCYB.2019.2937951

    Article  Google Scholar 

  8. Zhang, Z., Liang, H., Wu, C., Ahn, C.K.: Adaptive event-triggered output feedback fuzzy control for nonlinear networked systems with packet dropouts and actuator failure. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2891236

    Article  Google Scholar 

  9. Pan, Y., Yang, G.: Event-triggered fuzzy control for nonlinear networked control systems. Fuzzy Sets Syst. 329, 91–107 (2017)

    Article  MathSciNet  Google Scholar 

  10. Cao, L., Li, H., Dong, G., Lu, R.: Event-triggered control for multiagent systems with sensor faults and input saturation. IEEE Trans. Syst. Man Cybern. Syst. (2019). https://doi.org/10.1109/TSMC.2019.2938216

    Article  Google Scholar 

  11. Wang, Z., Xu, Y., Lu, R., Peng, H.: Finite-time state estimation for coupled markovian neural networks with sensor nonlinearities. IEEE Trans. Neural Netw. Learn. Syst. 28(3), 630–638 (2015)

    Article  MathSciNet  Google Scholar 

  12. Wu, C., Hu, Z., Liu, J., Wu, L.: Secure estimation for cyber-physical systems via sliding mode. IEEE Trans. Cybern. (2018). https://doi.org/10.1109/TCYB.2018.2825984

    Article  Google Scholar 

  13. Li, Y., Shao, X., Tong, S.: Adaptive fuzzy prescribed performance control of non-triangular structure nonlinear systems. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2937046

    Article  Google Scholar 

  14. Zhang, X., Li, X., Cao, J., Miaadi, F.: Design of memory controllers for finite-time stabilization of delayed neural networks with uncertainty. J. Frankl. Inst. 355(13), 5394–5413 (2018)

    Article  MathSciNet  Google Scholar 

  15. Zhai, D., An, L., Dong, J., Zhang, Q.: Output feedback adaptive sensor failure compensation for a class of parametric strict feedback systems. Automatica 97, 48–57 (2018)

    Article  MathSciNet  Google Scholar 

  16. Li, Y., Li, K., Tong, S.: Finite-time adaptive fuzzy output feedback dynamic surface control for mimo nonstrict feedback systems. IEEE Trans. Fuzzy Syst. 27(1), 96–110 (2018)

    Article  Google Scholar 

  17. Zhai, D., An, L., Ye, D., Zhang, Q.: Adaptive reliable \({H}_{\infty }\) static output feedback control against Markovian jumping sensor failures. IEEE Trans. Neural Netw. Learn. Syst. 29(3), 631–644 (2017)

    Article  MathSciNet  Google Scholar 

  18. Zhang, H., Yang, J., Su, C.: T-S fuzzy-model-based robust \({H}_{\infty }\) design for networked control systems with uncertainties. IEEE Trans. Ind. Inform. 3(4), 289–301 (2007)

    Article  Google Scholar 

  19. Li, F., Shi, P., Lim, C.C., Wu, L.: Fault detection filtering for nonhomogeneous Markovian jump systems via a fuzzy approach. IEEE Trans. Fuzzy Syst. 26(1), 131–141 (2018)

    Article  Google Scholar 

  20. Li, H., Yu, J., Hilton, C., Liu, H.: Adaptive sliding-mode control for nonlinear active suspension vehicle systems using T–S fuzzy approach. IEEE Trans. Ind. Electron. 60(8), 3328–3338 (2013)

    Article  Google Scholar 

  21. Ning, Z., Yu, J., Pan, Y., Li, H.: Adaptive event-triggered fault detection for fuzzy stochastic systems with missing measurements. IEEE Trans. Fuzzy Syst. 26(4), 2201–2212 (2017)

    Article  Google Scholar 

  22. Lam, H.K., Seneviratne, L.D.: Stability analysis of interval type-2 fuzzy-model-based control systems. IEEE Trans. Syst. Man Cybern. Part B Cybern. 38(3), 617–28 (2008)

    Article  Google Scholar 

  23. Lam, H.K., Li, H., Deters, C., Secco, E.L., Wurdemann, H.A., Althoefer, K.: Control design for interval type-2 fuzzy systems under imperfect premise matching. IEEE Trans. Ind. Electron. 61(2), 956–968 (2014)

    Article  Google Scholar 

  24. Lam, H.K., Narimani, M.: Stability analysis and performance design for fuzzy-model-based control system under imperfect premise matching. IEEE Trans. Fuzzy Syst. 17(4), 949–961 (2009)

    Article  Google Scholar 

  25. Zhang, Z., Zhou, Q., Wu, C., Li, H.: Dissipativity-based reliable interval type-2 fuzzy filter design for uncertain nonlinear systems. Int. J. Fuzzy Syst. 20(2), 390–402 (2018)

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  27. Rong, N., Wang, Z., Zhang, H.: Finite-time stabilization for discontinuous interconnected delayed systems via interval type-2 T–S fuzzy model approach. IEEE Trans. Fuzzy Syst. (2018). https://doi.org/10.1109/TFUZZ.2019.2891236

    Article  Google Scholar 

  28. Li, H., Gao, Y., Shi, P., Lam, H.K.: Observer-based fault detection for nonlinear systems with sensor fault and limited communication capacity. IEEE Trans. Autom. Control 61(9), 2745–2751 (2016)

    Article  MathSciNet  Google Scholar 

  29. Lam, H.K.: A review on stability analysis of continuous-time fuzzy-model-based control systems: from membership-function-independent to membership-function-dependent analysis. Eng. Appl. Artif. Intell. 67, 390–408 (2018)

    Article  Google Scholar 

  30. Su, X., Shi, P., Wu, L., Basin, M.V.: Reliable filtering with strict dissipativity for T–S fuzzy time-delay systems. IEEE Trans. Cybern. 44(12), 2470–2483 (2014)

    Article  Google Scholar 

  31. Pan, Y., Yang, G.: Event-driven fault detection for discrete-time interval type-2 fuzzy systems. IEEE Trans. Syst. Man Cybern. Syst. (2019). https://doi.org/10.1109/TSMC.2019.2945063

    Article  Google Scholar 

  32. Dong, H., Wang, Z., Ho, D.W., Gao, H.: Robust \({H}_{\infty }\) filtering for markovian jump systems with randomly occurring nonlinearities and sensor saturation: the finite-horizon case. IEEE Trans. Signal Process. 59(7), 3048–3057 (2011)

    Article  MathSciNet  Google Scholar 

  33. Zhao, Y., Sun, W., Gao, H.: Robust control synthesis for seat suspension systems with actuator saturation and time-varying input delay. J. Sound Vib. 329(21), 4335–4353 (2010)

    Article  Google Scholar 

  34. Yu, Y., Lam, H.K., Chan, K.Y.: T–S fuzzy-model-based output feedback tracking control with control input saturation. IEEE Trans. Fuzzy Syst. 26(6), 3514–3523 (2018)

    Article  Google Scholar 

  35. Liu, Y., Lee, S.M.: Stability and stabilization of Takagi–Sugeno fuzzy systems via sampled-data and state quantized controller. IEEE Trans. Fuzzy Syst. 24(3), 635–644 (2016)

    Google Scholar 

  36. Zhang, L., Liang, H., Sun, Y., Ahn, C.K.: Adaptive event-triggered fault detection scheme for semi-Markovian jump systems with output quantization. IEEE Trans. Syst. Man Cybern. Syst. (2019). https://doi.org/10.1109/TSMC.2019.2912846

    Article  Google Scholar 

  37. Lu, R., Xu, Y., Xue, A., Zheng, J.: Networked control with state reset and quantized measurements: observer-based case. IEEE Trans. Ind. Electron. 60(11), 5206–5213 (2012)

    Article  Google Scholar 

  38. Niu, Y., Ho, D.W., Li, C.: Filtering for discrete fuzzy stochastic systems with sensor nonlinearities. IEEE Trans. Fuzzy Syst. 18(5), 971–978 (2010)

    Article  Google Scholar 

  39. Gao, H., Meng, X., Chen, T., Lam, J.: Stabilization of networked control systems via dynamic output-feedback controllers. SIAM J. Control Optim. 48(5), 3643–3658 (2010)

    Article  MathSciNet  Google Scholar 

  40. Fu, M., Xie, L.: The sector bound approach to quantized feedback control. IEEE Trans. Autom. Control 50(11), 1698–1711 (2005)

    Article  MathSciNet  Google Scholar 

  41. Tseng, C., Chen, B.S., Uang, H.J.: Fuzzy tracking control design for nonlinear dynamic systems via T-S fuzzy model. IEEE Trans. Fuzzy Syst. 9(3), 381–392 (2001)

    Article  Google Scholar 

  42. Zhang, X., Han, Q., Wang, J.: Admissible delay upper bounds for global asymptotic stability of neural networks with time-varying delays. IEEE Trans. Neural Netw. Learn. Syst. 29(99), 1–11 (2018)

    MathSciNet  Google Scholar 

  43. Zhang, X., Han, Q., Wang, Z., Zhang, B.: Neuronal state estimation for neural networks with two additive time-varying delay components. IEEE Trans. Cybern. 47(10), 3184–3194 (2017)

    Article  Google Scholar 

  44. Li, X., Zhang, B., Li, P., Zhou, Q., Lu, R.: Finite-horizon \({H}_{\infty }\) state estimation for periodic neural networks over fading channels. IEEE Trans. Neural Netw. Learn. Syst. (2019). https://doi.org/10.1109/TNNLS.2019.2920368

    Article  Google Scholar 

  45. Liang, H., Zhang, L., Sun, Y., Huang, T.: Containment control of semi-Markovian multiagent systems with switching topologies. IEEE Trans. Syst. Man Cybern. Syst. (2019). https://doi.org/10.1109/TSMC.2019.2946248

    Article  Google Scholar 

  46. Zhou, Q., Wang, W., Liang, H., Basin, M., Wang, B.: Observer-based event-triggered fuzzy adaptive bipartite containment control of multi-agent systems with input quantization. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2953573

    Article  Google Scholar 

  47. Shen, W., Wang, J.: An integral terminal sliding mode control scheme for speed control system using a double-variable hydraulic transformer. ISA Trans. (2019). https://doi.org/10.1016/j.isatra.2019.08.068

    Article  Google Scholar 

  48. Xia, J., Zhang, J., Feng, J., Wang, Z., Zhuang, G.: Command filter-based adaptive fuzzy control for nonlinear systems with unknown control directions. IEEE Trans. Syst. Man Cybern. Syst. (2019). https://doi.org/10.1109/TSMC.2019.2911115

    Article  Google Scholar 

  49. Zhou, Q., Wang, W., Ma, H., Li, H.: Event-triggered fuzzy adaptive containment control for nonlinear multi-agent systems with unknown Bouc-Wen hysteresis input. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2961642

    Article  Google Scholar 

Download references

Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (61703051), and the Ph.D. Start-up Fund of Liaoning Province (20170520124), and the Project of Liaoning Province Science and Technology Program under Grant 2019-KF-03-13.

Author information

Authors and Affiliations

  1. College of Engineering, Bohai University, Jinzhou, 121013, Liaoning, China

    Qi Li & Yingnan Pan

  2. College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China

    Zhenxing Zhang

  3. Department of Engineering, King’s College London, Bush House, Strand campus, London, WC2R 2LS, UK

    Hak-Keung Lam

Authors
  1. Qi Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yingnan Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhenxing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hak-Keung Lam
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yingnan Pan.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Q., Pan, Y., Zhang, Z. et al. Reliable Dissipative Interval Type-2 Fuzzy Control for Nonlinear Systems with Stochastic Incomplete Communication Route and Actuator Failure. Int. J. Fuzzy Syst. 22, 368–379 (2020). https://doi.org/10.1007/s40815-020-00807-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-020-00807-y

Keywords

Search

Navigation