Skip to main content

Advertisement

Springer Nature Link
Log in

Dissipativity-based asynchronous control for time-varying delay T–S fuzzy Markov jump systems with multisource disturbances and input saturation

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

Abstract

In this paper, the problem of asynchronous dissipative control for a class of Takagi–Sugeno (T–S) fuzzy Markov jump systems with multiple sources disturbances is studied. Compared with the previous conclusions, the parameter uncertainty, time-varying delay and input saturation are taken into account in nonlinear system. And a new fuzzy disturbance rejection control structure is proposed by setting the disturbance observer and controller. The Hidden Markov model (HMM) is used to detect the mode information in the case that the modes mismatch between the system and controller, which ensures that the system is exponentially mean-square stable and has a satisfactory dissipative performance. Then, the sufficient conditions for the stability and dissipative of the augmented system are given in the form of linear matrix inequalities (LMIs), and the gain matrices of the observer and controller can be directly calculated. Finally, the practicability and effectiveness of the proposed method are verified by two examples.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Data availability

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

References

  1. Shi H, Li P, Cao J et al (2020) Robust Fuzzy Predictive Control for Discrete-Time Systems with Interval Time-Varying Delays and Unknown Disturbances. IEEE Trans Fuzzy Syst 28(7):1504–1516

    Google Scholar 

  2. Liu J, Yin T, Cao J et al (2021) Security Control for T-S Fuzzy Systems with Adaptive Event-Triggered Mechanism and Multiple Cyber-Attacks. IEEE Transactions on Systems, Man, and Cybernetics: Systems 51(10):6544–6554

    Article  Google Scholar 

  3. Ma X, Sun Z, He Y (1998) Analysis and Design of Fuzzy Controller and Fuzzy Observer. IEEE Trans Fuzzy Syst 6(1):41–51

    Article  Google Scholar 

  4. Tseng C, Chen B, Uang H (2001) Fuzzy Tracking Control Design for Nonlinear Dynamic Systems via T-S Fuzzy Model. IEEE Trans Fuzzy Syst 3(9):381–392

    Article  Google Scholar 

  5. Xie W, Zhang J, Li Y et al (2022) A Novel Polynomial Membership Functions Based Control Method for T-S Fuzzy Systems. ISA Trans 129:192–203

    Article  PubMed  Google Scholar 

  6. Su X, Shi P, Wu L et al (2013) A Novel Control Design on Discrete-Time Takagi-Sugeno Fuzzy Systems with Time-Varying Delays. IEEE Trans Fuzzy Syst 21(4):655–671

    Article  Google Scholar 

  7. Zhang K, Jiang B, Staroswiecki M (2010) Dynamic Output Feedback Fault Tolerant Controller Design for Takagi-Sugeno Fuzzy Systems with Actuator Faults. IEEE Trans Fuzzy Syst 1(18):194–201

    Article  Google Scholar 

  8. Ran G, Chen H, Li C, et al (2022) A Hybrid Design of Fault Detection for Nonlinear Systems Based on Dynamic Optimization. IEEE Transactions on Neural Networks and Learning Systems

  9. Chen P, Zhang D, Yu L et al (2022) Dynamic Event-Triggered Output Feedback Control for Load Frequency Control in Power Systems with Multiple Cyber Attacks. IEEE Transactions on Systems, Man, and Cybernetics: Systems 52(10):6246–6258

    Article  Google Scholar 

  10. Li L, Sun Z (2013) Dynamic Energy Control for Energy Efficiency Improvement of Sustainable Manufacturing Systems Using Markov Decision Process. IEEE Transactions on Systems, Man, and Cybernetics: Systems 43(5):1195–1205

    Article  Google Scholar 

  11. Lian B, Zhang Q, Li J (2018) Sliding Mode Control and Sampling Rate Strategy for Networked Control Systems with Packet Disordering via Markov Chain Prediction. ISA Trans 83:1–12

    Article  PubMed  Google Scholar 

  12. Zeng P, Deng F, Liu X et al (2021) Event-Triggered \(H_{\infty }\) Control for Network-Based Uncertain Markov Jump Systems Under DoS Attacks. J Franklin Inst 358:2895–2914

    Article  MathSciNet  Google Scholar 

  13. Rabiner LR (1989) A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. Proc IEEE 77(2):257–286

    Article  Google Scholar 

  14. Tao J, Lu R, Su H et al (2018) Asynchronous Filtering of Nonlinear Markov Jump Systems with Randomly Occurred Quantization via T-S Fuzzy Models. IEEE Trans Fuzzy Syst 4(26):1866–1877

    Google Scholar 

  15. Tao J, Xiao Z, Rao H et al (2022) Event-Triggered and Asynchronous Reduced-Order Filtering Codesign for Fuzzy Markov Jump Systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems 52(6):3937–3946

    Article  Google Scholar 

  16. Shen H, Li F, Yan H et al (2018) Finite-Time Event-Triggered \(H_{\infty }\) Control for T-S Fuzzy Markov Jump Systems. IEEE Trans Fuzzy Syst 26(5):3122–3135

    Article  Google Scholar 

  17. Wu Z, Dong S, Su H et al (2018) Asynchronous Dissipative Control for Fuzzy Markov Jump Systems. IEEE Transactions on Cybernetics 48(8):2426–2436

    Article  PubMed  Google Scholar 

  18. Dong S, Fang M, Shi P et al (2020) Dissipativity-Based Control for Fuzzy Systems with Asynchronous Modes and Intermittent Measurements. IEEE Transactions on Cybernetics 50(6):2389–2399

    Article  PubMed  Google Scholar 

  19. Dong S, Chen CLP, Fang M et al (2020) Dissipativity-Based Asynchronous Fuzzy Sliding Mode Control for T-S Fuzzy Hidden Markov Jump Systems. IEEE Transactions on Cybernetics 50(9):4020–4030

    Article  PubMed  Google Scholar 

  20. Ran G, Shu Z, Lam HK et al (2023) Dissipative Tracking Control of Nonlinear Markov Jump Systems with Incomplete Transition Probabilities: A Multiple-Event-Triggered Approach. IEEE Trans Fuzzy Syst 31(7):2389–2400

    Article  Google Scholar 

  21. Ran G, Liu J, Li C et al (2022) Fuzzy-Model-Based Asynchronous Fault Detection for Markov Jump Systems With Partially Unknown Transition Probabilities: An Adaptive Event-Triggered Approach. IEEE Trans Fuzzy Syst 30(11):4679–4689

    Article  Google Scholar 

  22. Zhou Q, Wu C, Shi P (2017) Observer-Based Adaptive Fuzzy Tracking Control of Nonlinear Systems with Time Delay and Input Saturation. Fuzzy Sets Syst 316:49–68

    Article  MathSciNet  Google Scholar 

  23. Zhao J, Wang J, Park JH et al (2015) Memory Feedback Controller Design for Stochastic Markov Jump Distributed Delay Systems with Input Saturation and Partially Known Transition Rates. Nonlinear Anal Hybrid Syst 15:52–62

    Article  MathSciNet  Google Scholar 

  24. Ghaffari V (2022) A Robust Predictive Observer-Based Integral Control Law for Uncertain LTI Systems under External Disturbance. J Franklin Inst 359:6915–6938

    Article  MathSciNet  Google Scholar 

  25. Zheng W, Zhang Z, Wang H et al (2020) Robust \(H_{\infty }\) Dynamic Output Feedback Control for Interval Type-2 T-S Fuzzy Multiple Time-Varying Delays Systems with External Disturbance. J Franklin Inst 357:3193–3218

    Article  MathSciNet  Google Scholar 

  26. Zhao Y, Pang M, Yu S et al (2021) \(H_{\infty }\) Finite-Time Composite Anti-Disturbance Switching Control for Switched Systems. ISA Trans 115:71–78

    Article  PubMed  Google Scholar 

  27. Zhang J, Shi P, Xia Y (2010) Robust Adaptive Sliding-Mode Control for Fuzzy Systems with Mismatched Uncertainties. IEEE Trans Fuzzy Syst 18(4):700–711

    Article  CAS  Google Scholar 

  28. Qi W, Zong G, Karimi HR (2020) Sliding Mode Control for Nonlinear Stochastic Singular Semi-Markov Jump Systems. IEEE Trans Autom Control 65(1):361–368

    Article  MathSciNet  Google Scholar 

  29. Zhang H, Wei X, Karimi HR et al (2018) Anti-disturbance control based on disturbance observer for nonlinear systems with bounded disturbances. J Franklin Inst 355(2018):4916–4930

    Article  MathSciNet  Google Scholar 

  30. Yao X, Lian Y, Park JH (2019) Disturbance-observer-based event-triggered control for semi-Markovian jump nonlinear systems. Appl Math Comput 363:124597

    MathSciNet  Google Scholar 

  31. Fan Z, Adhikary AC, Li S et al (2022) Disturbance observer based inverse optimal control for a class of nonlinear systems. Neurocomputing 500:821–831

    Article  Google Scholar 

  32. You L, Wei X, Han J et al (2020) Elegant anti-disturbance control for stochastic systems with multiple heterogeneous disturbances based on fuzzy logic systems. Trans Inst Meas Control 42(14):2611–2621

    Article  Google Scholar 

  33. Kavikumar R, Kwon OM, Sakthivel R et al (2022) Sliding Mode Control for IT2 Fuzzy Semi-Markov Systems with Faults and Disturbances. Appl Math Comput 423:127028

    MathSciNet  Google Scholar 

  34. Xu T, Zhu C, Qi W et al (2022) Passive analysis and finite-time anti-disturbance control for semi-Markovian jump fuzzy systems with saturation and uncertainty. Appl Math Comput 424:127030

    MathSciNet  Google Scholar 

  35. Kavikumar R, Kwon OM, Kaviarasan B et al (2023) Antidisturbance Control Design for Interval Type-2 Fuzzy Stochastic Systems With Input Quantization. IEEE Trans Fuzzy Syst 31(6):1806–1818

    Article  Google Scholar 

  36. Han X, Ma Y, Fu L (2020) Finite-time dynamic output-feedback dissipative control for singular uncertainty T-S fuzzy systems with actuator saturation and output constraints. J Franklin Inst 357(8):4543–4573

    Article  MathSciNet  Google Scholar 

  37. Han X, Wu K, Yao Y (2022) Asynchronous boundary stabilization for T-S fuzzy Markov jump delay reaction-diffusion neural networks. J Franklin Inst 359:2833–2856

    Article  MathSciNet  Google Scholar 

  38. Zhang N, Chen H, Li W (2021) Stability for multi-links stochastic delayed complex networks with semi-Markov jump under hybrid multi-delay impulsive control. Neurocomputing 449:214–228

    Article  Google Scholar 

  39. Shi P, Su X, Li F (2016) Dissipativity-based filtering for fuzzy switched systems with stochastic perturbation. IEEE Trans Autom Control 61(6):1694–1699

    Article  MathSciNet  Google Scholar 

  40. Lu Z, Ran G, Xu F et al (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 

Download references

Acknowledgements

This project was supported in part by the National Natural Science Foundation of China Nos. 61273004 and 62103126, and in part by the Natural Science Foundation of Hebei province Nos. F2021203061, F2020201014 and A2019203403.

Author information

Authors and Affiliations

  1. School of Science, Yanshan University, Qinhuangdao, 066004, Hebei, People’s Republic of China

    Yuxin Guo, Xu Ma & Yuechao Ma

  2. School of Electronic Information Engineering, Hebei University, Baoding, 071002, Hebei, People’s Republic of China

    Lei Fu

Authors
  1. Yuxin Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xu Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yuechao Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lei Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuechao Ma.

Ethics declarations

Conflict of interest

The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

Additional information

Publisher's Note

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

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

Guo, Y., Ma, X., Ma, Y. et al. Dissipativity-based asynchronous control for time-varying delay T–S fuzzy Markov jump systems with multisource disturbances and input saturation. Int. J. Mach. Learn. & Cyber. 15, 1343–1359 (2024). https://doi.org/10.1007/s13042-023-01971-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13042-023-01971-x

Keywords