Skip to main content
Log in

Mixed \(H_{\infty }\) and passivity analysis for T-S fuzzy system with non-fragile memory sampled-data control via augment Lyapunov–Krasovskii functional

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

Abstract

The performance of mixed \(H_{\infty }\) and passivity for T-S fuzzy system under the non-fragile memory sampled-data controller is considered in this paper. We construct a non-fragile memory sampled-data controller, which includes a constant signal transmission delay. And by constructing an augment Lyapunov–Krasovskii functional (LKF), taking into account Wirtinger-based integral inequality and the Convex combination technique, we can get a new criteria that mixed \(H_{\infty }\) and passivity for closed-loop system. Numerical examples are used to demonstrate the effectiveness and superiority of the results.

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

Similar content being viewed by others

References

  1. Takagi T, Sugeno M (1985) Fuzzy identification of systems and its applications to modeling and control. IEEE Trans Syst Man and Cybernet 15(1):116–132

    Article  Google Scholar 

  2. Zhao X, Lin C, Chen B, Wang Q (2018) A novel Lyapunov–Krasovskii functionalal approach to stability and stabilization for T-S fuzzy systems with time delay. Neurocomputing 313:288–294

    Article  Google Scholar 

  3. Wang Y, Shen H, Karimi H, Duan D (2018) Dissipativity-based fuzzy integral sliding mode control of continuous-time T-S fuzzy systems. IEEE Trans Fuzzy Syst 26(3):1164–1176

    Article  Google Scholar 

  4. Tang P, Ma Y (2019) Exponential stabilization and sampled-data control for uncertain T-S fuzzy systems with time-varying delay. J Franklin Inst 356:4859–4887

    Article  MathSciNet  Google Scholar 

  5. Shen H, Dai M, Luo Y, Cao J (2020) Fault-tolerant fuzzy control for semi-Markov jump nonlinear systems subject to incomplete SMK and actuator failures. IEEE Trans Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2020.3011760

    Article  Google Scholar 

  6. Wang J, Xia J, Shen H, Xing M, Park J (2020) Synchronization for fuzzy Markov jump chaotic systems with piecewise-constant transition probabilities subject to PDT switching rule. IEEE Trans Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2020.3012761

    Article  Google Scholar 

  7. Xia Y, Wang J, Meng B, Chen X (2020) Further results on fuzzy sampled-data stabilization of chaotic nonlinear systems. Appl Math Comput 379:125225

    MathSciNet  MATH  Google Scholar 

  8. Pan Y, Du P, Xue H, Lam H (2020) Singularity-free fixed-time fuzzy control for robotic systems with user-defined performance. IEEE Trans Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2020.2999746

    Article  Google Scholar 

  9. Du P, Pan Y, Li H, Lam H (2020) Nonsingular finite-time event-triggered fuzzy control for large-scale nonlinear systems. IEEE Trans Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2020.2992632

    Article  Google Scholar 

  10. Park M, Kwon O, Ryu J (2018) Advanced stability criteria for linear systems with time-varying delays. J Franklin Inst 355(1):520–543

    Article  MathSciNet  Google Scholar 

  11. Yu H, Ma Y, Liu J (2019) Extended dissipative analysis for uncertain T-S fuzzy system with time-varying delay and randomly occurring gain variations. J Franklin Inst 356(15):8542–8568

    Article  MathSciNet  Google Scholar 

  12. Zhao W, Ma Y, Chen A, Zhang Y (2019) Robust sliding mode control for Markovian jump singular systems with randomly changing structure. Appl Math Comput 349:81–96

    MathSciNet  MATH  Google Scholar 

  13. Liang H, Liu G, Zhang H, Huang T (2020) Neural-network-based event-triggered adaptive control of nonaffine nonlinear multiagent systems with dynamic uncertainties. IEEE Trans Neural Netw Learn Syst. https://doi.org/10.1109/TNNLS.2020.3003950

    Article  Google Scholar 

  14. Kim H, Park J, Joo Y (2018) Sampled-data control of fuzzy systems based on the intelligent digital redesign technique: an input-delay approach. Int J Control Auto Syst 16(1):327–334

    Article  Google Scholar 

  15. Rathinasamy S, Sa K, Boomipalagan K, Alzahrani F (2018) Dissipativity-based non-fragile sampled-data control design of interval type-2 fuzzy systems subject to random delays. ISA Trans 83:154–164

    Article  Google Scholar 

  16. Vimal Kumar S, Raja R, Marshal Anthoni S (2018) Robust finite-time non-fragile sampled-data control for T-S fuzzy flexible spacecraft model with stochastic actuator faults. Appl Math Comput 321:483–497

    MathSciNet  MATH  Google Scholar 

  17. Sakthivel R, Saravanakumar T, Ma Y, Marshal Anthoni S (2017) Finite-time resilient reliable sampled-data control for fuzzy systems with randomly occurring uncertainties. Fuzzy Sets Syst 329:1–18

    Article  MathSciNet  Google Scholar 

  18. Samidurai R, Sriraman R (2019) Non-fragile sampled-data stabilization analysis for linear systems with probabilistic time-varying delays. J Franklin Inst 356(8):4335–4357

    Article  MathSciNet  Google Scholar 

  19. Kin H, Park J, Joo Y (2018) A fuzzy Lyapunov–Krasovskii functional approach to sampled-data output-feedback stabilization of polynomial fuzzy systems. IEEE Trans Fuzzy Syst 26(1):366–373

    Article  Google Scholar 

  20. Ge C, Shi Y, Park J (2019) Robust stabilization for T-S fuzzy systems with time-varying delays and memory sampled-data control. Appl Math Comput 346:500–512

    MathSciNet  MATH  Google Scholar 

  21. Luo J, Liu X, Tian W (2020) A new approach to generalized dissipativity analysis for fuzzy systems with coupling memory sampled-data control. Appl Math Comput 368:124774

    MathSciNet  MATH  Google Scholar 

  22. Liu Y, Guo B, Park J, Lee S (2018) Non-fragile exponential synchronization of delayed complex dynamical networks with memory sampled-Data control. IEEE Trans Neural Netw Learn Syst 29(1):118–128

    Article  MathSciNet  Google Scholar 

  23. Shi K, Wang J, Zhong S (2019) Non-fragile memory fltering of T-S fuzzy delayed neural networks based on switched fuzzy sampled-data control. Fuzzy Sets Syst. https://doi.org/10.1016/j.fss.2019.09.001

    Article  Google Scholar 

  24. Park M, Kwon O, Ryu J (2017) Advanced stability criteria for linear systems with time-varying delays. J Franklin Inst 355(1):520–543

    Article  MathSciNet  Google Scholar 

  25. Wang L, Liu J (2018) Local stability analysis for continuous-time Takagi–Sugeno fuzzy systems with time delay. Neurocomputing 273:152–158

    Article  Google Scholar 

  26. Seuret A, Liu K, Gouaisbaut F (2018) Generalized reciprocally convex combination lemmas and its application to time-delay systems. Automatica 95:488–493

    Article  MathSciNet  Google Scholar 

  27. Liu Y, Park J, Guo B, Shu Y (2018) Further results on stabilization of chaotic systems based on fuzzy memory sampled-data control. IEEE Trans Fuzzy Syst 26(2):1040–1045

    Article  Google Scholar 

  28. Zeng H, Teo K, He Y (2019) Sampled-data-based dissipative control of T-S fuzzy systems. Appl Math Comput 65:415–427

    MathSciNet  MATH  Google Scholar 

  29. Wang Y, Karimi H, Lam H-K, Shen H (2018) An improved result on exponential stabilization of sampled-Data fuzzy systems. IEEE Trans Fuzzy Syst 26(6):3875–3883

    Article  Google Scholar 

  30. Zhao J, Liu W, Zhang G (2018) Sampled-data based quantisation control for T-S fuzzy switched systems with actuator failures dependent on an improved Lyapunov functional method. IET Control Theory Appl 12(17):2368–2379

    Article  MathSciNet  Google Scholar 

  31. Cheng J, Park J, Liu Y (2017) Finite-time fuzzy control of nonlinear Markovian jump delayed systems with partly uncertain transition descriptions. Fuzzy Sets Syst 314:99–115

    Article  MathSciNet  Google Scholar 

  32. Ma Y, Jia X, Zhang Q (2018) Robust observer-based finite-time control for discrete-time singular Markovian jumping system with time delay and actuator saturation. Nonlinear Anal Hybrid Syst 28:1–22

    Article  MathSciNet  Google Scholar 

  33. Yang G, Xie J, Kao Y, Wang C (2017) Robust non-fragile control for delayed singular Markovian jump systems with actuator saturation and partially unknown transition probabilities. Int J Robust Nonlinear Control 27:2669–2687

    Article  MathSciNet  Google Scholar 

  34. Du X, Yang Z, Jin Z, Xia C, Bao D (2018) A comparative study of passive control on flow structure evolution and convective heat transfer enhancement for impinging jet. Int J Heat Mass Transfer 126:256–280

    Article  Google Scholar 

  35. Eljajeh Y, Petkovski M (2018) Self-adaptive approach for optimisation of passive control systems for seismic resistant buildings. Original Res Paper 16:3171–3194

    Google Scholar 

  36. Chen J, Lin C, Chen B, Wang Q (2017) Mixed and passive control for singular systems with time delay via static output feedback. Appl Math Comput 293:244–253

    MathSciNet  MATH  Google Scholar 

  37. Shen H, Su L, Park J (2017) Reliable mixed /passive control for T-S fuzzy delayed systems based on a semi-Markov jump model approach. Fuzzy Sets Syst 314:79–98

    Article  MathSciNet  Google Scholar 

  38. Zheng Q, Zhang H, Ling Y, Guo X (2018) Mixed \(H_{\infty }\) and passive control for a class of nonlinear switched systems with average dwell time via hybrid control approach. J Franklin Inst 355:1156–1175

    Article  MathSciNet  Google Scholar 

  39. Zheng Q, Zhang H (2018) Mixed and passive filtering for switched Takagi-Sugeno fuzzy systems with average dwell time. ISA Trans 75:52–63

    Article  Google Scholar 

  40. Huo S, Chen M, Shen H (2017) Non-fragile mixed and passive asynchronous state estimation for Markov jump neural networks with randomly occurring uncertainties and sensor nonlinearity. Neurocomputing 227:46–53

    Article  Google Scholar 

  41. Sakthivel R, Saravanakumar T, Ma Y, Anthoni S (2017) Finite-time resilient reliable sampled-data control for fuzzy systems with randomly occurring uncertainties. Fuzzy Sets Syst 329:1–18

    Article  MathSciNet  Google Scholar 

  42. Wang Y, Hu X, Shi K, Song X, Shen H (2020) Network-based passive estimation for switched complex dynamical networks under persistent dwell-time with limited signals. J Franklin Inst 357:10921–10936

    Article  MathSciNet  Google Scholar 

  43. Seuret A, Gouaisbaut F (2013) Wirtinger-based integral inequality: application to time-delay systems. Automatica 49(9):2860–2866

    Article  MathSciNet  Google Scholar 

  44. Zeng H, Park J, Xia J, Xiao S (2014) Improved delay-dependent stability criteria for T-S fuzzy systems with time-varying delay. Appl Math Comput 235:492–501

    MathSciNet  MATH  Google Scholar 

  45. Yoneyama J (2010) Robust control of uncertain fuzzy systems under time-varying sampling. Fuzzy Sets Syst 161:859–871

    Article  MathSciNet  Google Scholar 

  46. Yoneyama J (2012) Robust sampled-data stabilization of uncertain fuzzy systems via input delay approach. Inf Sci 198:169–176

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

The authors would like to express their gratitude to the editor and the anonymous referees for their valuable suggestions that have greatly improved the quality of the paper.

Funding

This research was supported by National Natural Science Foundation of China (Grant 61273004).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yuechao Ma.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, Y., Ma, Y. Mixed \(H_{\infty }\) and passivity analysis for T-S fuzzy system with non-fragile memory sampled-data control via augment Lyapunov–Krasovskii functional. Int. J. Mach. Learn. & Cyber. 12, 2933–2945 (2021). https://doi.org/10.1007/s13042-021-01379-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13042-021-01379-5

Keywords

Navigation