Skip to main content
SpringerLink
Log in

T–S Fuzzy-Based Security Control of Nonlinear Unmanned Marine Vehicle Systems with Uncertain Stochastic DoS Attack

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

Abstract

This paper is concerned with the output tracking control for a class of network-based nonlinear unmanned marine vehicle (UMV) systems subject to denial-of-service (DoS) attacks, where a Takagi–Sugeno (T–S) fuzzy approach is proposed to grapple with the nonlinearity of UMV. A semi-Markov chain is introduced to reveal the switches of different attack degrees on actuators. The transition probabilities (TPs) and the sojourn-time probability density functions (ST-PDFs) of the introduced semi-Markov chain are partially unavailable because of unpredictable DoS attacks. Through introducing the upper bound of the sojourn time for each attack mode and giving an enlarged known threshold to unavailable TPs and/or ST-PDFs, the sufficient conditions for the \(\sigma\)-mean square stability (\(\sigma\)-MSS) with performance of output tracking system are derived in the form of linear matrix inequalities (LMIs). Attack-tolerant controllers are then designed to overcome those stochastic DoS attacks. Finally, the effectiveness of the proposed control scheme is verified by a simulation study.

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
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Wang, Y., Han, Q.: Network-based heading control and rudder oscillation reduction for unmanned surface vehicles. IEEE Trans. Control Syst. Technol. 25(5), 1609–1620 (2017)

    Article  Google Scholar 

  2. Liang, X., Qu, X., Hou, Y., Li, Y., Zhang, R.: Distributed coordinated tracking control of multiple unmanned surface vehicles under complex marine environments. Ocean Engineering, 205, https://doi.org/10.1016/j.oceaneng.2020.107328(2020)

  3. Chwa, D.: Global Tracking control of underactuated ships with input and velocity constraints using dynamic surface control method. IEEE Trans. Control Syst. Technol. 19(6), 1357–1370 (2011)

    Article  Google Scholar 

  4. Du, J., Hu, X., Krstić, M., Sun, Y.: Dynamic positioning of ships with unknown parameters and disturbances. Control. Eng. Pract. 76, 22–30 (2018)

    Article  Google Scholar 

  5. Zhang, D., Ye, Z., Chen, P., Wang, Q.: Intelligent event-based output feedback control with Q-learning for unmanned marine vehicle systems. Control Eng. Pract. 105, https://doi.org/10.1016/j.conengprac.2020.104616(2020)

  6. Feng, H., Zhang, B., Li, Q., Tang, G.: Delayed fuzzy output feedback \({H_\infty }\) control for offshore structures. Journal of Marine Science and Engineering, 8(6), https://doi.org/10.3390/jmse8060434(2020)

  7. Wang, N., Qian, C., Sun, J.C., Liu, Y.C.: Adaptive robust finite-time trajectory tracking control of fully actuated marine surface vehicles. IEEE Trans. Control Syst. Technol. 24, 1454–1462 (2016)

    Article  Google Scholar 

  8. Karimi, H.R., Lu, Y.: Guidance and control methodologies for marine vehicles: a survey. Control Eng. Pract. 111, https://doi.org/10.1016/j.conengprac.2021.104785(2021)

  9. Wang, N., Ahn, C.K.: Coordinated trajectory-tracking control of a marine aerial-surface heterogeneous system. IEEE Trans. Mechatron. 26(6), 3198–3210 (2021)

    Article  Google Scholar 

  10. Wang, N., Gao, Y., Zhang, X.: Data-driven performance-prescribed reinforcement learning control of an unmanned surface vehicle. IEEE Trans. Neural Netw. Learn. Syst. 32(12), 5456–5467 (2021)

    Article  MathSciNet  Google Scholar 

  11. Wang, N., Zhang, Y., Ahn, C.K., Xu, Q.: Autonomous pilot of unmanned surface vehicles: bridging path planning and tracking. IEEE Trans. Veh. Techol. https://doi.org/10.1109/TVT.2021.3136670 (2021)

  12. Wang, N., Gao, Y., Zhao, H., Ahn, C.K.: Reinforcement learning-based optimal tracking control of an unknown unmanned surface vehicle. IEEE Trans. Neural Netw. Learn. Syst. 32(7), 3034–3045 (2021)

    Article  MathSciNet  Google Scholar 

  13. Wang, N., Gao, Y., Liu, Y., Li, K.: Self-learning-based optimal tracking control of an unmanned surface vehicle with pose and velocity constraints. International Journal of Robust and Nonlinear Control, https://doi.org/10.1002/rnc.5978(2021)

  14. Ding, D., Wang, Z., Ho, D.W.C., Wei, G.: Observer-based event-triggering consensus control for multiagent systems with lossy sensors and cyber-attacks. IEEE Trans. Cybern. 47(8), 1936–1947 (2017)

    Article  Google Scholar 

  15. González, A., Cuenca, Á., Salt, J., Jacobs, J.: Robust stability analysis of an energy-efficient control in a networked control system with application to unmanned ground vehicles. Inf. Sci. 578, 64–84 (2021)

    Article  MathSciNet  Google Scholar 

  16. Wang, Y., Han, Q.: Network-based modeling and dynamic output feedback control for unmanned marine vehicles in network environments. Automatica 91, 43–53 (2018)

    Article  MATH  Google Scholar 

  17. Mastani, E., Rahmani, M.: Dynamic output feedback control for networked systems subject to communication delays, packet dropouts, and quantization. J. Franklin Inst. 358, 4304–4325 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  18. Dong, Z., Bao, T., Zheng, M., Yang, X., Song, L., Mao, Y.: Heading control of unmanned marine vehicles based on an improved robust adaptive fuzzy neural network control algorithm. IEEE Access 7, 9704–9713 (2019)

    Article  Google Scholar 

  19. Hao, L., Yu, Y., Li, H.: Fault tolerant control of UMV based on sliding mode output feedback. Appl. Math. Comput. 359, 433–455 (2019)

    MathSciNet  MATH  Google Scholar 

  20. Hao, L., Zhang, H., Yue, W., Li, H.: Fault-tolerant compensation control based on sliding mode technique of unmanned marine vehicles subject to unknown persistent ocean disturbances. Int. J. Control Autom. Syst. 18(3), 739–752 (2020)

    Article  Google Scholar 

  21. Chang, W.J., Lian, K.Y., Su, C.L., Tsai, M.H.: Multi-constrained fuzzy control for perturbed T-S fuzzy singular systems by proportional-plus-derivative state feedback method. Int. J. Fuzzy Syst. 23, 1972–1985 (2021)

    Article  Google Scholar 

  22. Lv, X., Fei, J., Sun, Y.: Fuzzy PID controller design for uncertain networked control systems based on T-S fuzzy model with random delays. Int. J. Fuzzy Syst. 21, 571–582 (2019)

    Article  MathSciNet  Google Scholar 

  23. Wang, N., Sun, Z., Su, S.F., Wang, Y.: Fuzzy uncertainty observer-based path-following control of underactuated marine vehicles with unmodeled dynamics and disturbances. Int. J. Fuzzy Syst. 20, 2593–2604 (2018)

    Article  MathSciNet  Google Scholar 

  24. Yin, J., Wang, N., Perakis, A.N.: A real-time sequential ship roll prediction scheme based on adaptive sliding data window. IEEE Trans. Syst. Man Cybern. Syst. 48, 2115–2125 (2018)

    Article  Google Scholar 

  25. Sun, K., Qiu, J., Karimi, H.R., Fu, Y.: Event-triggered robust fuzzy adaptive finite-time control of nonlinear systems with prescribed performance. IEEE Trans. Fuzzy Syst. 29, 1460–1471 (2021)

    Article  Google Scholar 

  26. Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control. IEEE Trans. Syst. Man Cyber. SMC–15(1), 116–32 (1985)

    Article  MATH  Google Scholar 

  27. Wang, Y., Han, Q., Fei, M., Peng, C.: Network-based T-S fuzzy dynamic positioning controller design for unmanned marine vehicles. IEEE Trans. Cybern. 48(9), 2750–2763 (2018)

    Article  Google Scholar 

  28. Zhang, D., Feng, G., Wang, Q.G., Shi, Y., Vasilakos, A.V.: A survey on attack detection, estimation and control of industrial cyber-physical systems. ISA Trans. 116, 1–16 (2021)

    Article  Google Scholar 

  29. Zhang, D., Feng, G., Shi, Y., Srinivasan, D.: Physical safety and cyber security analysis of multi-agent systems: a survey of recent advances. IEEE/CAA J. Autom. Sin. 8(2), 319–333 (2021)

    Article  MathSciNet  Google Scholar 

  30. Zhang, D., Ye, Z.H., Feng, G., Li, H.Y.: Intelligent event-based fuzzy dynamic positioning control of nonlinear unmanned marine vehicles under DoS attack. IEEE Trans. Cybern. https://doi.org/10.1109/TCYB.2021.3128170 (2021)

  31. Ye, Z., Zhang, D., Wu, Z.: Adaptive event-based tracking control of unmanned marine vehicle systems with DoS attack. J. Franklin Inst. 358(3), 1915–1939 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  32. Ye, Z., Zhang, D., Wu, Z., Yan, H.: A3C-based intelligent event-triggering control of networked nonlinear unmanned marine vehicles subject to hybrid attacks. IEEE Trans. Intell. Transport. Syst. https://doi.org/10.1109/TITS.2021.3118648 (2021)

  33. Zhang, D., Ye, Z.H., Dong, X.W.: Co-design of fault detection and consensus control protocol for multi-agent systems under hidden DoS attack. IEEE Trans. Circ. Syst. I 68(5), 2158–2170 (2021)

    MathSciNet  Google Scholar 

  34. Befekadu, G.K., Gupta, V., Antsaklis, P.J.: Risk-sensitive control under markov modulated denial-of-service (DoS) attack strategies. IEEE Trans. Autom. Control 60(12), 3299–3304 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  35. Shi, D., Elliott, R.J., Chen, T.: On finite-state stochastic modeling and secure estimation of cyber-physical systems. IEEE Trans. Autom. Control 62(1), 65–80 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  36. Zonouz, S., Rogers, K.M., Berthier, R., Bobba, R.B., Sanders, W.H., Overbye, T.J.: SCPSE: security-oriented cyber-physical state estimation for power grid critical infrastructures. IEEE Trans. Smart Grid 3(4), 1790–1799 (2012)

    Article  Google Scholar 

  37. He, H., Chen, Y., Qi, W., Wang, M., Chen, X.: Observer-based resilient control of positive systems with heterogeneous DoS attacks: a markov model approach. Journal of the Franklin Institute, https://doi.org/10.1016/j.jfranklin.2021.04.034(2021)

  38. Zhang, L., Leng, Y., Colaneri, P.: Stability and stabilization of discrete-time semi-markov jump linear systems via semi-markov kernel approach. IEEE Trans. Autom. Control 61(2), 503–508 (2016)

    MathSciNet  MATH  Google Scholar 

  39. Ning, Z., Zhang, L., Colaneri, P.: Semi-markov jump linear systems with incomplete sojourn and transition information: analysis and synthesis. IEEE Trans. Autom. Control 65(1), 159–174 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  40. Tian, Y., Yan, H., Zhang, H., Zhan, X., Peng, Y.: Resilient static output feedback control of linear semi-markov jump systems with incomplete semi-markov kernel. IEEE Trans. Autom. Control 66(9), 4274–4281 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  41. Zhang, L., Yang, T., Shi, P., Liu, M.: Stability and stabilization of a class of discrete-time fuzzy systems with semi-Markov stochastic uncertainties. IEEE Trans. Syst. Man Cybern. 46(12), 1642–1653 (2016)

    Article  Google Scholar 

  42. Zhang, J., Shi, P., Qiu, J., Nguang, S.K.: A novel observer-based output feedback controller design for discrete-time fuzzy systems. IEEE Trans. Fuzzy Syst. 23, 223–229 (2015)

    Article  Google Scholar 

  43. Ju, Z., Zhang, H., Tan, Y.: Deception attack detection and estimation for a local vehicle in vehicle platooning based on a modified UFIR estimator. IEEE Internet Things J. 7(5), 3693–3705 (2020)

    Article  Google Scholar 

  44. Gao, L., Li, F., Fu, J.: Event-triggered output feedback resilient control for NCSs under deception attacks. Int. J. Control Autom. Syst. 18(9), 2572–2579 (2020)

    Article  Google Scholar 

  45. Li, X., Wang, B., Zhang, L., Ma, X.: \({H_\infty }\) Control with multiple packets compensation scheme for T-S fuzzy systems subject to cyber attacks. Int. J. Control Autom. Syst. 19(1), 230–240 (2021)

  46. Gao, L., Fu, J., Li, F.: Output-based security control of NCSs under resilient event-triggered mechanism and DoS attacks. Int. J. Control Autom. Syst. 19(4), 1519–1527 (2021)

    Article  Google Scholar 

  47. Ju, Z., Zhang, H., Tan, Y.: Distributed deception attack detection in platoon-based connected vehicle systems. IEEE Trans. Veh. Technol. 69(5), 4609–4620 (2020)

    Article  Google Scholar 

  48. Deng, C., Zhang, D., Feng, G.: Resilient practical cooperative output regulation for MASs with unknown switching exosystem dynamics under DoS attacks. Automatica. https://doi.org/10.1016/j.automatica.2022.110172 (2022)

Download references

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant No. 61873237, the Natural Science Foundation of Zhejiang Province under Grant No. LR22F030003, and the Fundamental Research Funds for the Provincial Universities of Zhejiang under Grant No. RF-A2019003.

Author information

Author notes

  1. Zehua Ye and Dan Zhang have contributed equally to this work.

Authors and Affiliations

  1. Department of Automation, Zhejiang University of Technology, Hangzhou, 310023, China

    Jiahao Dong, Zehua Ye, Dan Zhang & Fanghong Guo

Authors
  1. Jiahao Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zehua Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fanghong Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dan Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dong, J., Ye, Z., Zhang, D. et al. T–S Fuzzy-Based Security Control of Nonlinear Unmanned Marine Vehicle Systems with Uncertain Stochastic DoS Attack. Int. J. Fuzzy Syst. 25, 289–301 (2023). https://doi.org/10.1007/s40815-022-01311-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-022-01311-1

Keywords

Search

Navigation