Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Self-Triggered \(H_\infty \) Control for Uncertain Nonlinear Networked Control Systems Under Dynamic Quantization and Packet Dropout

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

Abstract

This paper aims to address the problem of packet dropout and limited bandwidth in networked control systems (NCSs) and takes Lyapunov stability theory and linear matrix inequality (LMI) as basic tools. Then, the output feedback \(H_\infty \) control problem for a class of discrete-time nonlinear NCSs with dynamic quantization and packet dropout via the self-triggered mechanism (STM) is investigated. The Takagi-Sugeno (T-S) fuzzy model is introduced to represent the considered discrete-time nonlinear system. The dynamic quantization strategy in which the quantization parameters can be on-line adjusted is designed, and a Bernoulli process to represent the packet dropout phenomenon is introduced. In addition, the STM which possesses the distinctive feature of predicting the next triggered instant according to the current output of the system is presented. A condition of the closed-loop stability for NCS and the existence condition of the observer-based controller satisfying \(H_\infty \) performance are obtained by applying the Lyapunov method and cone complementary linearization approach, respectively. Finally, a simulation of continuous stirred tank reactor system is carried out to verify the effectiveness of the provided method.

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

Similar content being viewed by others

Explore related subjects

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

References

  1. Yang, H., Li, P., Xia, Y., Yan, C.: \(h_\infty \) static output feedback for low-frequency networked control systems with a decentralized event-triggered scheme. IEEE Trans. Cybern. 51(8), 4227–4236 (2021)

    Article  PubMed  Google Scholar 

  2. Lee, M.-Y., Chen, B.-S., Tsai, C.-Y., Hwang, C.-L.: Stochastic \(h_\infty \) robust decentralized tracking control of large-scale team formation uav network system with time-varying delay and packet dropout under interconnected couplings and wiener fluctuations. IEEE Access 9, 41976–4199 (2021)

    Article  Google Scholar 

  3. Yang, H., Li, P., Xia, Y., Yan, Y.: Double-loop stability for high frequency networked control systems subject to actuator saturation. IEEE Trans. Cybern. 9(4), 1454–1462 (2019)

    Article  Google Scholar 

  4. Rahnama, A., Xia, M., Antsaklis, P.J.: A qsr-dissipativity based design for event-triggered networked systems. IEEE Trans. Autom. Control 64(6), 2590–2597 (2019)

    Article  MathSciNet  Google Scholar 

  5. Li, M., She, J., Liu, Z.-T., Wu, M., Ohyama, Y.: Suppression of packet losses and disturbances in networked control systems based on equivalent-input-disturbance approach. IEEE Trans. Cybern. (2021). https://doi.org/10.1109/TCYB.2021.3080581

    Article  PubMed  PubMed Central  Google Scholar 

  6. Jin, Q., Wu, S., Zhang, R., Lu, R.: Improved minmax control for industrial networked systems over imperfect communication. IEEE Trans. Syst. Man Cybern. Syst. 50(4), 1310–1317 (2020)

    Article  Google Scholar 

  7. Qiu, L., Dai, L., Ahsan, U., Fang, C., Najariyan, M., Pan, J.F.: Model predictive control for networked multiple linear motors system under dos attack and time delay. IEEE Trans. Ind. Inf. (2021). https://doi.org/10.1109/TII.2021.3139127

    Article  Google Scholar 

  8. Lee, H.-W., Kwon, W., Park, J., Han, S.: A more configurable finite memory event triggering control scheme for networked control systems. IEEE Access 8, 171078–171090 (2020)

    Article  Google Scholar 

  9. Bikas, L.N., Rovithakis, G.A.: Tracking performance guarantees in the presence of quantization for uncertain nonlinear systems. IEEE Trans. Autom. Control 66(7), 3311–3316 (2021)

    Article  MathSciNet  Google Scholar 

  10. Zanma, T., Ohtsuka, T., Liu, K.: Set-based state estimation in quantized state feedback control systems with quantized measurements. IEEE Trans. Control Syst. Technol. 28(2), 550–557 (2020)

    Article  Google Scholar 

  11. Li, Z.-M., Chang, X.-H., Park, J.H.: Quantized static output feedback fuzzy tracking control for discrete-time nonlinear networked systems with asynchronous event-triggered constraints. IEEE Trans. Syst. Man Cybern. Syst. 51(6), 3820–3831 (2021)

    Article  Google Scholar 

  12. Chen, C.-Y., Gui, W.-H., Wu, L., Liu, Z., Yan, H.: Tracking performance limitations of MIMO networked control systems with multiple communication constraints. IEEE Trans. Cybern. 50(7), 2982–2995 (2020)

    Article  PubMed  Google Scholar 

  13. Li, B., Wang, Z., Han, Q., Liu, H.: Input-to-state stabilization in probability for nonlinear stochastic systems under quantization effects and communication protocols. IEEE Trans. Cybern. 49(9), 3242–3254 (2019)

    Article  PubMed  Google Scholar 

  14. Tang, X., Deng, L., Yu, J., Qu, H.: Output feedback predictive control of interval type-2 t-s fuzzy systems with Markovian packet loss. IEEE Trans. Fuzzy Syst. 26(4), 2450–2459 (2018)

    Article  Google Scholar 

  15. Cai, X., Shi, K., She, K., Zhong, Z., Tang, Y.: Quantized sampled-data control tactic for t-s fuzzy NCS under stochastic cyber-attacks and its application to truck-trailer system. IEEE Trans. Veh. Technol. 71(7), 7023–7032 (2022)

    Article  Google Scholar 

  16. Yu, C., You, K., Xie, L.: Quantized identification of ARMA systems with colored measurement noise. Automatica 66, 101–108 (2016)

    Article  MathSciNet  Google Scholar 

  17. Xing, L., Wen, C., Zhu, Y., Su, H., Liu, Z.: Output feedback control for uncertain nonlinear systems with input quantization. Automatica 65, 191–202 (2016)

    Article  MathSciNet  Google Scholar 

  18. Abdelrahim, M., Dolk, V.S., Heemels, W.P.M.H.: Event-triggered quantized control for input-to-state stabilization of linear systems with distributed output sensors. IEEE Trans. Autom. Control 64(12), 4952–4967 (2019)

    Article  MathSciNet  Google Scholar 

  19. Zheng, Q., Xu, S., Du, B.: Quantized guaranteed cost output feedback control for nonlinear networked control systems and its applications. IEEE Trans. Fuzzy Syst. 30(7), 2402–2411 (2022)

    Article  Google Scholar 

  20. Zanma, T., Azegami, M., Liu, K.: Optimal input and quantization interval for quantized feedback system with variable quantizer. IEEE Trans. Ind. Electron. 64(3), 2246–2254 (2017)

    Article  Google Scholar 

  21. Yue, B.-F., Su, M.-Y., Jin, X.-Z., Che, W.-W.: Event-triggered MFAC of nonlinear NCSS against sensor faults and dos attacks. IEEE Trans. Circuits Syst. II Express Briefs 69(11), 4409–4413 (2022). https://doi.org/10.1109/TCSII.2022.3178881

    Article  Google Scholar 

  22. Zhang, Y., Sun, J., Liang, H., Li, H.: Event-triggered adaptive tracking control for multi-agent systems with unknown disturbances. IEEE Trans. Cybern. 50(3), 890–901 (2020)

    Article  PubMed  Google Scholar 

  23. Hu, S., Yue, D., Cheng, Z., Tian, E., Xie, X., Chen, X.: Co-design of dynamic event-triggered communication scheme and resilient observer-based control under aperiodic dos attacks. IEEE Trans. Cybern. 51(9), 4591–4601 (2021)

    Article  PubMed  Google Scholar 

  24. Liu, D., Yang, G., Er, M.J.: Event-triggered control for t-s fuzzy systems under asynchronous network communications. IEEE Trans. Fuzzy Syst. 28(2), 390–399 (2020)

    Article  ADS  Google Scholar 

  25. 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. 27(9), 1793–1806 (2019)

    Article  Google Scholar 

  26. Li, W., Xie, Z., Zhao, J., Chu, S., Wong, P.K., Gao, J.: Improved AET robust control for networked T-S fuzzy systems with asynchronous constraints. IEEE Trans. Cybern. 52(3), 1465–1478 (2022)

    Article  PubMed  Google Scholar 

  27. Wang, X., Sun, J., Wang, G., Dou, L.: A mixed switching event-triggered transmission scheme for networked control systems. IEEE Trans. Control Netw. Syst. 9(1), 390–402 (2022)

    Article  MathSciNet  CAS  Google Scholar 

  28. Dai, L., Cannon, M., Yang, F., Yan, S.: Fast self-triggered MPC for constrained linear systems with additive disturbances. IEEE Trans. Autom. Control 66(8), 3624–3637 (2021)

    Article  MathSciNet  Google Scholar 

  29. Qi, X., Zeng, P.-L., Bao, W.: Event-triggered and self-triggered \(h_\infty \) control of uncertain switched linear systems. IEEE Trans. Syst. Man Cybern. Syst. 50(4), 1442–1454 (2020)

    Article  Google Scholar 

  30. Peng, C., Han, Q.-L.: On designing a novel self-triggered sampling scheme for networked control systems with data losses and communication delays. IEEE Trans. Ind. Electron. 63(2), 1239–1248 (2015)

    Article  Google Scholar 

  31. Tang, Y., Gao, H., Kurths, J.: Robust \(h_{\infty }\) self-triggered control of networked systems under packet dropouts. IEEE Trans. Cybern. 46(12), 3294–3305 (2016)

    Article  PubMed  Google Scholar 

  32. Li, Q., Yao, F., Zhong, X., Xu, G.: Output feedback guaranteed cost control for networked control systems with random packet dropouts and time delays in forward and feedback communication links. IEEE Trans. Autom. Sci. Eng. 13(1), 284–295 (2016)

    Article  Google Scholar 

  33. Tang, X., Deng, L., Qu, H.: Predictive control for networked interval type-2 t-s fuzzy system via an event-triggered dynamic output feedback scheme. IEEE Trans. Fuzzy Syst. 27(8), 1573–1586 (2018)

    Article  Google Scholar 

  34. Tang, X., Deng, L.: Multi-step output feedback predictive control for uncertain discrete-time t-s fuzzy system via event-triggered scheme. Automatica 107, 362–370 (2019)

    Article  MathSciNet  Google Scholar 

  35. Zheng, Q., Xu, S., Du, B.: Asynchronous resilent state estimation of switched fuzzy systems with multiple state impulsive jumps. IEEE Trans. Cybern. (2023). https://doi.org/10.1109/TCYB.2023.3253161

    Article  PubMed  Google Scholar 

Download references

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant 61871061; in part by the Research Project of Chongqing Science and Technology Commission under Grant cstc2021jcyjmsxmX0315; and in part by the Project of Advanced Scientific Research Institute of CQUPT under Grant E011A2022329.

Author information

Author notes

  1. Na Wei, Xiao Lv and Zidi Xia have contributed equally to this work.

Authors and Affiliations

  1. The College of Automation and the Advanced Scientific Research Institute, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Na Wei, Xiaoming Tang & Zidi Xia

  2. The Chongqing Special Equipment Inspection and Research Institute, Chongqing, 400065, China

    Xiao Lv

  3. Key Laboratory of Electromechanical Equipment Security in Western Complex Environment for State Market Regulation, Chongqing, 400065, China

    Xiao Lv

Authors
  1. Na Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaoming Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiao Lv
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zidi Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiaoming Tang.

Ethics declarations

Conflict of interest

All authors declare that there is no conflict of interest.

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

Wei, N., Tang, X., Lv, X. et al. Self-Triggered \(H_\infty \) Control for Uncertain Nonlinear Networked Control Systems Under Dynamic Quantization and Packet Dropout. Int. J. Fuzzy Syst. 26, 527–539 (2024). https://doi.org/10.1007/s40815-023-01612-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-023-01612-z

Keywords

Search

Navigation