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Network-Based \(H_\infty \) Filtering for Descriptor Markovian Jump Systems with a Novel Neural Network Event-Triggered Scheme

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Abstract

This paper studies network-based \(H_\infty \) filtering problem for descriptor Markovian jump systems with a novel neural network event-triggered scheme. Firstly, to save more limited communication bandwidth, a novel neural network event-triggered scheme is introduced to dynamically adjust communication bandwidth based on desired filtering performance. Secondly, an event-triggered mode-dependent \(H_\infty \) filter is designed for descriptor Markovian jump system. By considering the network-induced delay and the event-triggered scheme, a delay system method is used to build a novel filtering error system model. By using Lyapunov function technology and free weighting method, the criteria are obtained in terms of LMIs which guarantee the filtering error system to be regular, impulse free and stochastically stable with the \(H_\infty \) performance. Then, a co-design method is proposed for the designed filter parameters. Finally, a numerical simulation example is employed to illustrate the effectiveness, and by a compared example, we show that the number of transmitted data produced by the proposed neural network event-triggered scheme is less than those produced by traditional event-triggered scheme.

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References

  1. Siqueira A, Terra M (2009) A fault-tolerant manipulator robot based on \({H}_2\), \({H}_{\infty }\), and mixed \({H}_2\), \({H}_{\infty }\) Markovian Controls. IEEE/ASME Trans Mechatron 44(2):257–263

    Article  Google Scholar 

  2. Costa O, Araujo M (2008) A generalized multi-period mean variance portfolio optimization with Markov switching parameters. Automatica 44(10):2487–2497

    Article  MathSciNet  Google Scholar 

  3. Zhang Y, Zhang QL, Zhang JY, Wang YY (2020) Sliding mode control for fuzzy singular systems with time delay based on vector integral sliding mode Surface. IEEE Trans Fuzzy Syst 28(4):768–782

    Article  Google Scholar 

  4. Ma PM, Zhang HC (2009) Robust stability and \({H}_{\infty }\) control for uncertain discrete Markovian jump singular systems with mode-dependent time-delay. Int J Robust Nonlinear Control 19(9):965–985

    Article  MathSciNet  Google Scholar 

  5. Xu S, Lam J, Mao X (2007) Delay-dependent \({H}_{\infty }\) control and filtering for uncertain Markovian jump systems with time-varying delays. IEEE Trans Circuits Syst I Regul Pap 54(9):2070–2077

    Article  MathSciNet  Google Scholar 

  6. Cao JL, Shu Z, Xu S, Boukas KE (2007) Robust control of descriptor discrete-time Markovian jump systems. Int J Control 80(3):374–385

    Article  MathSciNet  Google Scholar 

  7. Wang Y, Shi P, Wang Q, Duan D (2013) Exponential \({H}_{\infty }\) filtering for singular Markovian jump systems with mixed mode-dependent time-varying delay. Circuits Syst I Regul Pap IEEE Trans 60(9):2440–2452

    Article  MathSciNet  Google Scholar 

  8. Li JH, Zhang QL, Yan XG, Spurgeon KS (2016) Integral sliding mode control for Markovian jump T-S fuzzy descriptor systems based on the super-twisting algorithm. Iet Control Theory Appl 11(8):1134–1143

    Article  MathSciNet  Google Scholar 

  9. Tian FY, Wang SZ (2020) Finite-time extended dissipative filtering for singular T-S fuzzy systems with nonhomogenous Markov jumps. IEEE Trans Cybern. https://doi.org/10.1109/TCYB.2020.3030503

    Article  Google Scholar 

  10. Yue D, Han LQ (2004) Robust \({H}_{\infty }\) filter design of uncertain descriptor systems with discrete and distributed delays. IEEE Trans Signal Process 52(11):3200–3212

    Article  MathSciNet  Google Scholar 

  11. Wang GL, Zhang QL, Yang CY (2013) Exponential \({H}_{\infty }\) filtering for singular Markovian jump parameters. Int J Robust Nonlinear Control 23

  12. Lin FX, Fei SM, Shen J (2011) Delay-dependent filtering for discrete-time singular Markovian jump systems with time-varying delay and partially unknown transition probabilities. Signal Process 91(2):277–289

    Article  Google Scholar 

  13. Xia XF, Zheng WX, Xu SY (2019) Event-triggered filter design for Markovian jump delay systems with nonlinear perturbation using quantized measurement. Int J Robust Nonlinear Control. https://doi.org/10.1002/rnc.4645

    Article  MathSciNet  MATH  Google Scholar 

  14. Xiao XQ, Zhou L, Daniel WC, Lu GP (2018) Event-triggered control of continuous-time switched linear systems. IEEE Trans Autom Control 1–1

  15. Xu QY, Zhang YJ, Zhang BY (2018) Network-based event-triggered \({H}_{\infty }\) filtering for discrete-time singular Markovian jump systems. Signal Process 145:106–115

    Article  Google Scholar 

  16. Zhang XM, Han QL, Zhang BY (2015) Event-based \({H}_{\infty }\) filtering for sampled-data system. Automatica 51:55–69

    Article  MathSciNet  Google Scholar 

  17. Zhang XM, Han QL, Alexandre S, Gouaisbaut F, He Y (2019) Overview of recent advances in stability of linear systems with time-varying delays. IET Control Theory Appl 13(1):1–16

    Article  MathSciNet  Google Scholar 

  18. Tian YF, Wang ZS (2020) A new multiple integral inequality and its application to stability analysis of time-delay systems. Appl Math Lett. https://doi.org/10.1016/j.aml.2020.106325

    Article  MathSciNet  MATH  Google Scholar 

  19. Wang YZ, Zhang T, Ren JC, Chen M (2019) Observer-based event-triggered sliding mode control for uncertain descriptor systems with a neural-network event-triggering sampling scheme. Neurocomputing. https://doi.org/10.1016/j.neucom.2019.12.066

    Article  Google Scholar 

  20. Peng C, Han QL, Yue D (2013) To transmit or not to transmit: a discrete event-triggered communication scheme for networked Takagi Sugeno fuzzy systems. IEEE Trans Fuzzy Syst 21:164–170

    Article  Google Scholar 

  21. Heemels WP, Donkers MC (2013) Periodic event-triggered control for linear systems. IEEE Trans Autom Control 58(4):847–861

    Article  MathSciNet  Google Scholar 

  22. Peng C, Han QL, Ding D, Wang Y, Zhang X (2020) Dynamic event-triggered distributed coordination control and its applications: a survey of trends and techniques. IEEE Trans Syst Man Cybern Syst 50(9):3112–3125

    Article  Google Scholar 

  23. Hu S, Zhang Y, Du Z (2012) Network-based \({H}_{\infty }\) tracking control with event-triggering sampling scheme. IET Control Theory Appl 6(4):533–544

    Article  MathSciNet  Google Scholar 

  24. Zhang XM, Han QL (2017) Event-triggered \({H}_{\infty }\) control for a class of nonlinear networked control systems using novel integral inequalities. Int J Robust Nonlinear Control 27:679–700

    Article  MathSciNet  Google Scholar 

  25. Yue D, Tian EG, Han QL (2013) A delay system method for designing event-triggered controllers of networked control systems. IEEE Trans Autom Control 58(2):475–481

    Article  MathSciNet  Google Scholar 

  26. Chen P, Tai CY (2013) Event-triggered communication and \({H}_{\infty }\) control co-design for networked control systems. Automatica 49(5):1326–1332

    Article  MathSciNet  Google Scholar 

  27. Wu LG, Gao YB, Liu JX, Li HY (2017) Event-triggered sliding mode control of stochastic systems via output feedback. Automatica 82:79–92

    Article  MathSciNet  Google Scholar 

  28. Zhang B, Han QL, Zhang X (2016) Event-triggered \({H}_{\infty }\) reliable control for offshore structures in network environments. J Sound Vib 368:1–21

    Article  Google Scholar 

  29. Song J, Niu YG, Xu J (2018) An event-triggered approach to sliding mode control of Markovian Jump Lur’e systems under hidden mode detections. IEEE Trans Syst Man Cybern Syst 1–12

  30. Liu JL, Liu QH, Jie G, Zhang YY (2016) Adaptive event-triggered \({H}_{\infty }\) filtering for T-S fuzzy system with time delay. Neurocomputing 189:86–94

    Article  Google Scholar 

  31. Peng C, Yang MJ, Zhang J, Fei MR, Hu SL (2017) Network-based \({H}_{\infty }\) control for T-S fuzzy systems with an adaptive event-triggered communication scheme. Fuzzy Sets Syst 329:61–76

    Article  MathSciNet  Google Scholar 

  32. Wang ZY, Zhang T, Ren CJ (2020) A novel adaptive event-triggering scheme for network descriptor systems with time-delay. Int J Robust Nonlinear Control. https://doi.org/10.1002/rnc.5211

    Article  MathSciNet  Google Scholar 

  33. Zhou G, Yue D, Liu FL, Ding ZT (2017) \({H}_{\infty }\) tracking control of nonlinear networked systems with a novel adaptive event-triggered communication scheme. J Franklin Inst 354(8):3540–3553

    Article  MathSciNet  Google Scholar 

  34. Zhang J, Peng C, Du DJ, Zheng M (2016) Adaptive event-triggered communication scheme for networked control systems with randomly occurring nonlinearities and uncertainties. Neurocomputing 174:475–482

    Article  Google Scholar 

  35. Wang YL, Shi P, Lim CC, Liu Y (2016) Event-triggered fault detection filter design for a continuous-time networked control system. IEEE Trans Cybern 46(12):3414–3426

    Article  Google Scholar 

  36. Li Q, Shen B, Liu Y, Liu Y (2016) Event-triggered \({H}_{\infty }\) state estimation for discrete-time neural networks with mixed time delays and sensor saturations. Neural Comput Appl

  37. Xie TT, Chen G, Liao X (2019) Event-triggered asynchronous distributed optimization algorithm with heterogeneous time-varying step-sizes. Neural Comput Appl 7–8

  38. Tian E, Yue D, Zhang Y (2009) Delay-dependent robust \({H}_{\infty }\) control for T-S fuzzy system with interval time-varying delay. Fuzzy Sets Syst 160(12):1708–1719

    Article  MathSciNet  Google Scholar 

  39. Feng ZG, Shi P (2017) Two equivalent sets: application to singular systems. Automatica 77:198–205

    Article  MathSciNet  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant 61673100, 61673099, and Automation for Process Industries Fundamental Research Funds, No. 2013ZCX02.

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Correspondence to Yuzhong Wang.

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Wang, Y., Zhang, T., Chen, S. et al. Network-Based \(H_\infty \) Filtering for Descriptor Markovian Jump Systems with a Novel Neural Network Event-Triggered Scheme. Neural Process Lett 53, 757–775 (2021). https://doi.org/10.1007/s11063-020-10417-2

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