Skip to main content
Log in

Distributed \({H_\infty }\) State Estimation in Sensor Network Subject to State and Communication Delays

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

The distributed \(H_\infty \) state estimation of delayed sensor network is dealt with in this paper. To deeply reflect the time-delay phenomenon in the process of information fusion, a model containing state time-varying delay and different communication delays is set up. Afterwards, a fresh Lyapunov–Krasovskii functional (LKF) is given, which contains different kinds of time delays, delay-dependent matrix and multiple integral terms. Meanwhile, in order to cooperate with the constructed LKF to bring down the conservatism of the result effectively, relaxed-function-based single integral inequality and convex combination are employed to estimate the functional derivative. Thus, a less conservative criterion is gained to guarantee the asymptotic stability with desirable attenuation level of the estimation error system. Several simulation examples are used to testify the validity of the proposed approach.

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

Similar content being viewed by others

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

References

  1. M.S. Ali, M. Usha, Z. Orman, S. Arik, Improved result on state estimation for complex dynamical networks with time varying delays and stochastic sampling via sampled-data control. Neural Netw. 114, 28–37 (2019)

    Article  Google Scholar 

  2. W. Bai, W. Xue, Y. Huang, H. Fang, On extended state based kalman filter design for a class of nonlinear time-varying uncertain systems. Sci. China Inf. Sci. 61(4), 042201 (2018)

    Article  MathSciNet  Google Scholar 

  3. Y. Bai, Z. Li, C. Huang, New \(h_\infty \) control approaches for interval time-delay systems with disturbances and their applications. ISA Trans. 65, 174–185 (2016)

    Article  Google Scholar 

  4. S. Corbellini, E. Di Francia, S. Grassini, L. Iannucci, L. Lombardo, M. Parvis, Cloud based sensor network for environmental monitoring. Measurement 118, 354–361 (2018)

    Article  Google Scholar 

  5. D. Ding, Z. Wang, H. Dong, H. Shu, Distributed \(h_\infty \) state estimation with stochastic parameters and nonlinearities through sensor networks: the finite-horizon case. Automatica 48(8), 1575–1585 (2012)

    Article  MathSciNet  Google Scholar 

  6. H. Dong, Z. Wang, H. Gao, Distributed \(h_\infty \) filtering for a class of markovian jump nonlinear time-delay systems over lossy sensor networks. IEEE Trans. Ind. Electron. 60(10), 4665–4672 (2012)

    Article  Google Scholar 

  7. R. Dong, Y. Chen, W. Qian, An improved approach to robust \(h_\infty \) filtering for uncertain discrete-time systems with multiple delays. Circuits Syst. Signal Process. 39(1), 65–82 (2020)

    Article  Google Scholar 

  8. X. Ge, Q.L. Han, Distributed event-triggered \(h_\infty \) filtering over sensor networks with communication delays. Inf. Sci. 291, 128–142 (2015)

    Article  MathSciNet  Google Scholar 

  9. M. Hedayati, M. Rahmani, Robust distributed \(h_\infty \) filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays. Int. J. Robust Nonlinear Control 30(2), 538–566 (2020)

    Article  MathSciNet  Google Scholar 

  10. K.S. Ko, W.I. Lee, P. Park, D.K. Sung, Delays-dependent region partitioning approach for stability criterion of linear systems with multiple time-varying delays. Automatica 87, 389–394 (2018)

    Article  MathSciNet  Google Scholar 

  11. O. Kwon, M.J. Park, J.H. Park, S.M. Lee, Improvement on the feasible region of \(h_\infty \) performance and stability for systems with interval time-varying delays via augmented lyapunov-krasivskii functional. J. Frankl. Inst. 353(18), 4979–5000 (2016)

    Article  Google Scholar 

  12. J.Y. Li, B. Zhang, R. Lu, Y. Xu, Robust distributed \(h_\infty \) state estimation for stochastic periodic systems over constraint sensor networks. IEEE Trans. Syst. Man Cybern. Syst. (2018)

  13. Q. Li, J. Du, S. Zhu, L. Xu, Adaptive multiple video sensors fusion based on decentralized kalman filter and sensor confidence. Sci. China Inf. Sci. 60(6), 062102 (2017)

    Article  Google Scholar 

  14. Q. Li, X. Liu, Q. Zhu, S. Zhong, D. Zhang, Distributed state estimation for stochastic discrete-time sensor networks with redundant channels. Appl. Math. Comput. 343, 230–246 (2019)

    MathSciNet  MATH  Google Scholar 

  15. Q. Li, B. Shen, Z. Wang, F.E. Alsaadi, A sampled-data approach to distributed \(h_\infty \) resilient state estimation for a class of nonlinear time-delay systems over sensor networks. J. Frankl. Inst. 354(15), 7139–7157 (2017)

    Article  MathSciNet  Google Scholar 

  16. Y. Li, T. Yang, S. Tong, Adaptive neural networks finite-time optimal control for a class of nonlinear systems. IEEE Trans. Neural Netw. Learn. Syst. (2019). https://doi.org/10.1109/TNNLS.2019.2955438

    Article  Google Scholar 

  17. J. Liang, Z. Wang, T. Hayat, A. Alsaedi, Distributed \(h_\infty \) state estimation for stochastic delayed 2-d systems with randomly varying nonlinearities over saturated sensor networks. Inf. Sci. 370, 708–724 (2016)

    Article  Google Scholar 

  18. W.J. Lin, Y. He, C.K. Zhang, M. Wu, Stability analysis of neural networks with time-varying delay: enhanced stability criteria and conservatism comparisons. Commun. Nonlinear Sci. Numer. Simul. 54, 118–135 (2018)

    Article  MathSciNet  Google Scholar 

  19. L. Muduli, D.P. Mishra, P.K. Jana, Application of wireless sensor network for environmental monitoring in underground coal mines: a systematic review. J. Netw. Comput. Appl. 106, 48–67 (2018)

    Article  Google Scholar 

  20. W. Qian, Y. Gao, Y. Yang, Global consensus of multiagent systems with internal delays and communication delays. IEEE Trans. Syst. Man Cybern. Syst. 49(10), 1961–1970 (2019)

    Article  Google Scholar 

  21. W. Qian, Y. Li, Y. Chen, W. Liu, \(l_2\)-\(l_\infty \) filtering for stochastic delayed systems with randomly occurring nonlinearities and sensor saturation. Int. J. Syst. Sci. 51(13), 2360–2377 (2020)

    Article  Google Scholar 

  22. W. Qian, Y. Li, Y. Zhao, Y. Chen, New optimal method for \(l_2\)-\(l_\infty \) state estimation of delayed neural networks. Neurocomputing 415, 258–265 (2020)

    Article  Google Scholar 

  23. W. Qian, L. Wang, M.Z. Chen, Local consensus of nonlinear multiagent systems with varying delay coupling. IEEE Trans. Syst. Man Cybern. Syst. 48(12), 2462–2469 (2018)

    Article  Google Scholar 

  24. W. Qian, W. Xing, S. Fei, \(h_\infty \) state estimation for neural networks with general activation function and mixed time-varying delays. IEEE Trans. Neural Netw. Learn. Syst. (2020). https://doi.org/10.1109/TNNLS.2020.3016120

    Article  Google Scholar 

  25. W. Qian, W. Xing, L. Wang, B. Li, New optimal analysis method to stability and \(h_\infty \) performance of varying delayed systems. ISA Trans. 93, 137–144 (2019)

    Article  Google Scholar 

  26. R. Saravanakumar, M.S. Ali, H. Huang, J. Cao, Y.H. Joo, Robust \(h_\infty \) state-feedback control for nonlinear uncertain systems with mixed time-varying delays. Int. J. Control Autom. Syst. 16(1), 225–233 (2018)

    Article  Google Scholar 

  27. K. Schilling, Perspectives for miniaturized, distributed, networked cooperating systems for space exploration. Robot. Auton. Syst. 90, 118–124 (2017)

    Article  Google Scholar 

  28. B. Shen, Z. Wang, Y.S. Hung, Distributed \(h_\infty \)-consensus filtering in sensor networks with multiple missing measurements: the finite-horizon case. Automatica 46(10), 1682–1688 (2010)

    Article  MathSciNet  Google Scholar 

  29. D. Tacconi, D. Miorandi, I. Carreras, F. Chiti, R. Fantacci, Using wireless sensor networks to support intelligent transportation systems. Ad Hoc Netw. 8(5), 462–473 (2010)

    Article  Google Scholar 

  30. Q. Tan, X. Dong, Q. Li, Z. Ren, Distributed event-triggered cubature information filtering based on weighted average consensus. IET Control Theory Appl. 12(1), 78–86 (2017)

    Article  Google Scholar 

  31. S. Tong, Y. Li, Robust adaptive fuzzy backstepping output feedback tracking control for nonlinear system with dynamic uncertainties. Sci. China Inf. Sci. 53(2), 307–324 (2010)

    Article  MathSciNet  Google Scholar 

  32. S. Tong, X. Min, Y. Li, Observer-based adaptive fuzzy tracking control for strict-feedback nonlinear systems with unknown control gain functions. IEEE Trans. Cybern. (2020). https://doi.org/10.1109/TCYB.2020.2977175

    Article  Google Scholar 

  33. H. Trinh et al., Refined jensen-based inequality approach to stability analysis of time-delay systems. IET Control Theory Appl. 9(14), 2188–2194 (2015)

    Article  MathSciNet  Google Scholar 

  34. S. Vasuhi, V. Vaidehi, Target tracking using interactive multiple model for wireless sensor network. Inf. Fusion 27, 41–53 (2016)

    Article  Google Scholar 

  35. X. Wan, Z. Wang, M. Wu, X. Liu, State estimation for discrete time-delayed genetic regulatory networks with stochastic noises under the round-robin protocols. IEEE Trans. Nanobiosci. 17(2), 145–154 (2018)

    Article  Google Scholar 

  36. D. Wang, Z. Wang, G. Li, W. Wang, Distributed filtering for switched nonlinear positive systems with missing measurements over sensor networks. IEEE Sens. J. 16(12), 4940–4948 (2016)

    Article  Google Scholar 

  37. S. Wang, Y. Wang, Y. Jiang, Y. Li, Event-triggered based distributed \(h_\infty \) consensus filtering for discrete-time delayed systems over lossy sensor network. Trans. Inst. Meas. Control 40(9), 2740–2747 (2018)

    Article  MathSciNet  Google Scholar 

  38. Z. Wang, Y. Niu, Distributed estimation and filtering for sensor networks (2011)

  39. F. Wu, L. Xu, S. Kumari, X. Li, An improved and anonymous two-factor authentication protocol for health-care applications with wireless medical sensor networks. Multimed. Syst. 23(2), 195–205 (2017)

    Article  Google Scholar 

  40. Y. Yu, S. Peng, X. Dong, Q. Li, Z. Ren, Uif-based cooperative tracking method for multi-agent systems with sensor faults. Sci. China Inf. Sci. 62(1), 10202 (2019)

    Article  MathSciNet  Google Scholar 

  41. Z. Zhang, J. Li, L. Liu, Distributed state estimation and data fusion in wireless sensor networks using multi-level quantized innovation. Sci. China Inf. Sci. 59(2), 1–15 (2016)

    Google Scholar 

  42. D. Zhao, S.X. Ding, H.R. Karimi, Y. Li, Y. Wang, On robust kalman filter for two-dimensional uncertain linear discrete time-varying systems: a least squares method. Automatica 99, 203–212 (2019)

    Article  MathSciNet  Google Scholar 

  43. Q. Zhou, P. Du, H. Li, R. Lu, J. Yang, Adaptive fixed-time control of error-constrained pure-feedback interconnected nonlinear systems. IEEE Trans. Syst. Man Cybern. Syst. (2020). https://doi.org/10.1109/TSMC.2019.2961371

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61973105), the Innovation Scientists and Technicians Troop Construction Projects of Henan Province (Grant No. CXTD2016054), Zhongyuan High Level Talents Special Support Plan (Grant No. 20420050027), the Fundamental Research Funds for the Universities of Henan Province (Grant No. NSFRF170501), Innovative Scientists and Technicians Team of Henan Provincial High Education (Grant No. 20IRTSTHN019).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yunji Zhao.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qian, W., Zhang, X., Zhao, Y. et al. Distributed \({H_\infty }\) State Estimation in Sensor Network Subject to State and Communication Delays. Circuits Syst Signal Process 40, 3227–3243 (2021). https://doi.org/10.1007/s00034-020-01627-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-020-01627-z

Keywords

Navigation