Skip to main content
SpringerLink
Log in

Mixed \( {\varvec{H}}_{\varvec{\infty}} \) and Passive Depth Control for Autonomous Underwater Vehicles with Fuzzy Memorized Sampled-Data Controller

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

Abstract

This paper investigates the depth control problem for autonomous underwater vehicles (AUVs) by developing a novel fuzzy memorized sampled-data controller. In particular, the mixed \(H_{\infty }\) and passive performance index is considered for disturbances in more practical underwater environments. By means of the Lyapunov–Krasovskii functional method, sufficient criteria are established such that the desired depth can be stabilized while satisfying the prescribed mixed \(H_{\infty }\) and passive performance. Then, the desired fuzzy memorized controller is designed in terms of linear matrix inequalities (LMIs). Finally, an illustrative example is provided for demonstrating the feasibility and effectiveness of our derived results.

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

Similar content being viewed by others

References

  1. Yuh, J.: Design and control of autonomous underwater robots: a survey. Auton. Robots 8(1), 7–24 (2000)

    Article  Google Scholar 

  2. Xiang, X., Yu, C., Zhang, Q.: Robust fuzzy 3D path following for autonomous underwater vehicle subject to uncertainties. Comput. Oper. Res. 84, 165–177 (2017)

    Article  MathSciNet  Google Scholar 

  3. Xiang, X., Yu, C., Niu, Z., Zhang, Q.: Subsea cable tracking by autonomous underwater vehicle with magnetic sensing guidance. Sensors 16(8), 1335 (2016)

    Article  Google Scholar 

  4. Zhang, Q., Lapierre, L., Xiang, X.: Distributed control of coordinated path tracking for networked nonholonomic mobile vehicles. IEEE Trans. Ind. Inform. 9(1), 472–484 (2013)

    Article  Google Scholar 

  5. Xiang, X., Lapierre, L., Jouvencel, B.: Smooth transition of AUV motion control: from fully-actuated to under-actuated configuration. Robot. Auton. Syst. 67, 14–22 (2015)

    Article  Google Scholar 

  6. Ma, C., Zeng, Q.: Distributed formation control of 6-DOF autonomous underwater vehicles networked by sampled-data information under directed topology. Neurocomputing 154, 33–40 (2015)

    Article  Google Scholar 

  7. Xiang, X., Yu, C., Zhang, Q.: On intelligent risk analysis and critical decision of underwater robotic vehicle. Ocean Eng. 140, 453–465 (2017)

    Article  Google Scholar 

  8. Lee, Y.I., Kim, Y.G., Kohout, L.J.: An intelligent collision avoidance system for AUVs using fuzzy relational products. Inf. Sci. 158, 209–232 (2004)

    Article  Google Scholar 

  9. Teo, K., An, E., Beaujean, P.P.J.: A robust fuzzy autonomous underwater vehicle (AUV) docking approach for unknown current disturbances. IEEE J. Ocean. Eng. 37(2), 143–155 (2012)

    Article  Google Scholar 

  10. Wang, J.S., Lee, C.G.: Self-adaptive recurrent neuro-fuzzy control of an autonomous underwater vehicle. IEEE Trans. Robot. Autom. 19(2), 283–295 (2003)

    Article  Google Scholar 

  11. Yang, T.C.: Networked control system: a brief survey. IEE Proc. Control Theory Appl. 153(4), 403–412 (2006)

    Article  Google Scholar 

  12. Gupta, R.A., Chow, M.Y.: Networked control system: overview and research trends. IEEE Trans. Ind. Electron. 57(7), 2527–2535 (2010)

    Article  Google Scholar 

  13. Montestruque, L.A., Antsaklis, P.: Stability of model-based networked control systems with time-varying transmission times. IEEE Trans. Autom. Control 49(9), 1562–1572 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  14. Zhang, L., Shi, Y., Chen, T., Huang, B.: A new method for stabilization of networked control systems with random delays. IEEE Trans. Autom. Control 50(8), 1177–1181 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  15. van de Wouw, N., Naghshtabrizi, P., Cloosterman, M.B.G., Hespanha, J.P.: Tracking control for sampled-data systems with uncertain time-varying sampling intervals and delays. Int. J. Robust Nonlinear Control 20(4), 387–411 (2010)

    MathSciNet  MATH  Google Scholar 

  16. Fridman, E., Seuret, A., Richard, J.P.: Robust sampled-data stabilization of linear systems: an input delay approach. Automatica 40(8), 1441–1446 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  17. Fridman, E.: A refined input delay approach to sampled-data control. Automatica 46(2), 421–427 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  18. Naghshtabrizi, P., Hespanha, J.P., Teel, A.R.: Exponential stability of impulsive systems with application to uncertain sampled-data systems. Syst. Control Lett. 57(5), 378–385 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  19. Jia, X., Zhao, J., Zhang, D.: L2-gain control for TS fuzzy systems over an event-triggered communication network using delay decomposition and deviation bounds of membership functions. Int. J. Fuzzy Syst. 18(5), 817–828 (2016)

    Article  MathSciNet  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  21. Lu, X.G., Liu, M., Liu, J.X.: Design and optimization of interval type-2 fuzzy logic controller for delta parallel robot trajectory control. Int. J. Fuzzy Syst. 19(1), 190–206 (2017)

    Article  Google Scholar 

  22. Li, H., Jing, X., Lam, H.K., Shi, P.: Fuzzy sampled-data control for uncertain vehicle suspension systems. IEEE Trans. Cybern. 44(7), 1111–1126 (2014)

    Article  Google Scholar 

  23. Li, J.H., Lee, P.M.: Design of an adaptive nonlinear controller for depth control of an autonomous underwater vehicle. Ocean Eng. 32(17), 2165–2181 (2005)

    Article  Google Scholar 

  24. Liu, Y., Park, J. H., Guo, B. Z., Shu, Y.: Further results on stabilization of chaotic systems based on fuzzy memory sampled-data control. IEEE Trans. Fuzzy Syst. doi:10.1109/TFUZZ.2017.2686364 (2017)

  25. Mathiyalagan, K., Park, J.H., Sakthivel, R., Anthoni, S.M.: Robust mixed \(H_{\infty }\) and passive filtering for networked Markov jump systems with impulses. Signal Process. 101, 162–173 (2014)

    Article  Google Scholar 

  26. Su, L., Shen, H.: Mixed \(H_{\infty }\)/passive synchronization for complex dynamical networks with sampled-data control. Appl. Math. Comput. 259, 931–942 (2015)

    Article  MathSciNet  Google Scholar 

  27. Shi, P., Zhang, Y., Chadli, M., Agarwal, R.K.: Mixed H-infinity and passive filtering for discrete fuzzy neural networks with stochastic jumps and time delays. IEEE Trans. Neural Netw. Learn. Syst. 27(4), 903–909 (2016)

    Article  MathSciNet  Google Scholar 

  28. Park, P., Ko, J.W., Jeong, C.: Reciprocally convex approach to stability of systems with time-varying delays. Automatica 47(1), 235–238 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  29. Jiang, X.: On sampled-data fuzzy control design approach for TCS model-based fuzzy systems by using discretization approach. Inf. Sci. 296, 307–314 (2015)

    Article  MATH  Google Scholar 

  30. Zhang, X., Xiao, Y., Zhang, G., Sun, X., Zhao, X.: Delay-independent stabilization of depth control for unmanned underwater vehicle. In: Proceedings of the 2016 IEEE International Conference on Mechatronics and Automation (ICMA 2016), pp. 2494–2499 (2016)

Download references

Acknowledgements

This work was supported by the Fundamental Research Funds for the Central Universities under Grant FRF-TP-15-115A1 and the National Natural Science Foundation of China under Grant 61703038.

Author information

Authors and Affiliations

  1. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, China

    Chao Ma

  2. State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Chao Ma, Hong Qiao & Erlong Kang

Authors
  1. Chao Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hong Qiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Erlong Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chao Ma.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ma, C., Qiao, H. & Kang, E. Mixed \( {\varvec{H}}_{\varvec{\infty}} \) and Passive Depth Control for Autonomous Underwater Vehicles with Fuzzy Memorized Sampled-Data Controller. Int. J. Fuzzy Syst. 20, 621–629 (2018). https://doi.org/10.1007/s40815-017-0404-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-017-0404-0

Keywords

Search

Navigation