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Finite-time control for a class of hybrid systems via quantized intermittent control

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Abstract

This paper considers the finite-time drive-response synchronization of stochastic nonlinear systems consisting of continuous-time and discrete-time subsystems. To save communication resources and reduce control cost, quantized controllers, which only work on continuous-time intervals, are designed. Owing to the hybrid characteristics of continuous- and discrete-time subsystems, existing finite-time stability theorems are not applicable. By developing novel analytical techniques, three criteria are derived to guarantee the finite-time synchronization. Moreover, the settling time is explicitly estimated. It is shown that the settling time is dependent not only on the control gains and systems’ initial conditions, but also on the control width and uncontrolled width. Numerical examples demonstrate the effectiveness of the theoretical analysis.

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References

  1. Davis G M. A wavelet-based analysis of fractal image compression. IEEE Trans Image Process, 1998, 7: 141–154

    MathSciNet  MATH  Google Scholar 

  2. Cao J D, Li R X. Fixed-time synchronization of delayed memristor-based recurrent neural networks. Sci China Inf Sci, 2017, 60: 032201

    Google Scholar 

  3. Wang Z X, Fan J B, Jiang G-P, et al. Consensus in nonlinear multi-agent systems with nonidentical nodes and sampled-data control. Sci China Inf Sci, 2018, 61: 122203

    MathSciNet  Google Scholar 

  4. Sundar S, Minai A A. Synchronization of randomly multiplexed chaotic systems with application to communication. Phys Rev Lett, 2000, 85: 5456–5459

    Google Scholar 

  5. Lang J, Tao R, Wang Y. The discrete multiple-parameter fractional Fourier transform. Sci China Inf Sci, 2010, 53: 2287–2299

    MathSciNet  MATH  Google Scholar 

  6. Liu X, Chen T. Synchronization of complex networks via aperiodically intermittent pinning control. IEEE Trans Automat Contr, 2015, 60: 3316–3321

    MathSciNet  MATH  Google Scholar 

  7. Zhong J, Lu J, Liu Y, et al. Synchronization in an array of output-coupled Boolean networks with time delay. IEEE Trans Neural Netw Learn Syst, 2014, 25: 2288–2294

    Google Scholar 

  8. Yang X, Lu J. Finite-time synchronization of coupled networks with Markovian topology and impulsive effects. IEEE Trans Automat Contr, 2016, 61: 2256–2261

    MathSciNet  MATH  Google Scholar 

  9. Yao F Q, Deng F Q. Stability of impulsive stochastic functional differential systems in terms of two measures via comparison approach. Sci China Inf Sci, 2012, 55: 1313–1322

    MathSciNet  MATH  Google Scholar 

  10. Yang X, Cao J. Exponential synchronization of delayed neural networks with discontinuous activations. IEEE Trans Circ Syst I, 2013, 60: 2431–2439

    MathSciNet  Google Scholar 

  11. Zhang W, Yang X, Xu C, et al. Finite-time synchronization of discontinuous neural networks with delays and mismatched parameters. IEEE Trans Neural Netw Learn Syst, 2018, 29: 3761–3771

    MathSciNet  Google Scholar 

  12. Wan X, Yang X, Tang R, et al. Exponential synchronization of semi-Markovian coupled neural networks with mixed delays via tracker information and quantized output controller. Neural Netw, 2019, 118: 321–331

    MATH  Google Scholar 

  13. Yang X, Li X, Lu J, et al. Synchronization of time-delayed complex networks with switching topology via hybrid actuator fault and impulsive effects control. IEEE Trans Cybern, 2019. doi: https://doi.org/10.1109/TCYB.2019.2938217

  14. Yang X, Ho D W C, Lu J, et al. Finite-time cluster synchronization of T-S fuzzy complex networks with discontinuous subsystems and random coupling delays. IEEE Trans Fuzzy Syst, 2015, 23: 2302–2316

    Google Scholar 

  15. Bhat S P, Bernstein D S. Finite-time stability of continuous autonomous systems. SIAM J Control Opt, 2000, 38: 751–766

    MathSciNet  MATH  Google Scholar 

  16. Amato F, Ariola M, Dorato P. Finite-time control of linear systems subject to parametric uncertainties and disturbances. Automatica, 2001, 37: 1459–1463

    MATH  Google Scholar 

  17. Yang X, Lam J, Ho D W C, et al. Fixed-time synchronization of complex networks with impulsive effects via nonchattering control. IEEE Trans Automat Contr, 2017, 62: 5511–5521

    MathSciNet  MATH  Google Scholar 

  18. Shi P, Su X, Li F. Dissipativity-based filtering for fuzzy switched systems with stochastic perturbation. IEEE Trans Automat Contr, 2016, 61: 1694–1699

    MathSciNet  MATH  Google Scholar 

  19. Liu T, Jiang Z P. Further results on quantized stabilization of nonlinear cascaded systems with dynamic uncertainties. Sci China Inf Sci, 2016, 59: 072202

    Google Scholar 

  20. Yang X S, Cao J D, Xu C, et al. Finite-time stabilization of switched dynamical networks with quantized couplings via quantized controller. Sci China Technol Sci, 2018, 61: 299–308

    Google Scholar 

  21. Yang X, Lu J, Ho D W C, et al. Synchronization of uncertain hybrid switching and impulsive complex networks. Appl Math Model, 2018, 59: 379–392

    MathSciNet  MATH  Google Scholar 

  22. Cao J D, Rakkiyappan R, Maheswari K, et al. Exponential H filtering analysis for discrete-time switched neural networks with random delays using sojourn probabilities. Sci China Technol Sci, 2016, 59: 387–402

    Google Scholar 

  23. Yang X, Feng Z, Feng J, et al. Synchronization of discrete-time neural networks with delays and Markov jump topologies based on tracker information. Neural Netw, 2017, 85: 157–164

    MATH  Google Scholar 

  24. Zhai G, Lin H, Michel A N, et al. Stability analysis for switched systems with continuous-time and discrete-time subsystems. In: Proceedings of the 2004 American Control Conference, Boston, 2004. 4555–4560

  25. Zhai G, Lin H, Xu X, et al. Stability analysis and design of switched normal systems. In: Proceedings of the 43rd IEEE Conference Decision and Control, Atlantis, 2004. 3253–3258

  26. Zhai G S, Liu D R, Imae J, et al. Lie algebraic stability analysis for switched systems with continuous-time and discrete-time subsystems. IEEE Trans Circ Syst II, 2006, 53: 152–156

    Google Scholar 

  27. Zheng Y, Wang L. Consensus of switched multiagent systems. IEEE Trans Circ Syst II, 2016, 63: 314–318

    Google Scholar 

  28. Lin X, Zheng Y. Finite-time consensus of switched multiagent systems. IEEE Trans Syst Man Cybern Syst, 2017, 47: 1535–1545

    Google Scholar 

  29. Yang X, Cao J. Stochastic synchronization of coupled neural networks with intermittent control. Phys Lett A, 2009, 373: 3259–3272

    MATH  Google Scholar 

  30. Huang T, Li C, Yu W, et al. Synchronization of delayed chaotic systems with parameter mismatches by using intermittent linear state feedback. Nonlinearity, 2009, 22: 569–584

    MathSciNet  MATH  Google Scholar 

  31. Pan L, Cao J. Stochastic quasi-synchronization for delayed dynamical networks via intermittent control. Commun Nonlin Sci Numer Simul, 2012, 17: 1332–1343

    MathSciNet  MATH  Google Scholar 

  32. Zhang W, Li C, Huang T, et al. Stability and synchronization of memristor-based coupling neural networks with time-varying delays via intermittent control. Neurocomputing, 2016, 173: 1066–1072

    Google Scholar 

  33. Liu L, Perc M, Cao J D. Aperiodically intermittent stochastic stabilization via discrete time or delay feedback control. Sci China Inf Sci, 2019, 62: 072201

    MathSciNet  Google Scholar 

  34. Zhang W, Huang J, Wei P. Weak synchronization of chaotic neural networks with parameter mismatch via periodically intermittent control. Appl Math Model, 2011, 35: 612–620

    MathSciNet  MATH  Google Scholar 

  35. Xu C, Yang X, Lu J, et al. Finite-time synchronization of networks via quantized intermittent pinning control. IEEE Trans Cybern, 2018, 48: 3021–3027

    Google Scholar 

  36. Nesic D, Liberzon D. A unified framework for design and analysis of networked and quantized control systems. IEEE Trans Automat Contr, 2009, 54: 732–747

    MathSciNet  MATH  Google Scholar 

  37. Wang Z, Shen B, Shu H, et al. Quantized H control for nonlinear stochastic time-delay systems with missing measurements. IEEE Trans Automat Contr, 2012, 57: 1431–1444

    MathSciNet  MATH  Google Scholar 

  38. Xiao X, Zhou L, Zhang Z. Synchronization of chaotic Lur’e systems with quantized sampled-data controller. Commun Nonlin Sci Numer Simulat, 2014, 19: 2039–2047

    MathSciNet  MATH  Google Scholar 

  39. Liu Z, Wang F, Zhang Y, et al. Fuzzy adaptive quantized control for a class of stochastic nonlinear uncertain systems. IEEE Trans Cybern, 2016, 46: 524–534

    Google Scholar 

  40. Yang X, Zhu Q, Huang C. Lag stochastic synchronization of chaotic mixed time-delayed neural networks with uncertain parameters or perturbations. Neurocomputing, 2011, 74: 1617–1625

    Google Scholar 

  41. Yang X, Cao J, Lu J. Stochastic synchronization of complex networks with nonidentical nodes via hybrid adaptive and impulsive control. IEEE Trans Circ Syst I, 2012, 59: 371–384

    MathSciNet  Google Scholar 

  42. Tang Z, Park J H, Lee T H, et al. Mean square exponential synchronization for impulsive coupled neural networks with time-varying delays and stochastic disturbances. Complexity, 2016, 21: 190–202

    MathSciNet  Google Scholar 

  43. Zhang W, Li C, Huang T, et al. Fixed-time synchronization of complex networks with nonidentical nodes and stochastic noise perturbations. Phys A-Stat Mech Appl, 2018, 492: 1531–1542

    MathSciNet  Google Scholar 

  44. Liang J L, Wang Z D, Liu Y R, et al. Robust synchronization of an array of coupled stochastic discrete-time delayed neural networks. IEEE Trans Neural Netw, 2008, 19: 1910–1921

    Google Scholar 

  45. Tang Y, Fang J, Xia M, et al. Synchronization of Takagi-Sugeno fuzzy stochastic discrete-time complex networks with mixed time-varying delays. Appl Math Model, 2010, 34: 843–855

    MathSciNet  MATH  Google Scholar 

  46. Wang Z D, Wang Y, Liu Y R. Global synchronization for discrete-time stochastic complex networks with randomly occurred nonlinearities and mixed time delays. IEEE Trans Neural Netw, 2010, 21: 11–25

    Google Scholar 

  47. Yang X, Cao J, Lu J. Synchronization of randomly coupled neural networks with Markovian jumping and time-delay. IEEE Trans Circ Syst I, 2013, 60: 363–376

    MathSciNet  Google Scholar 

  48. Yang X, Cao J. Finite-time stochastic synchronization of complex networks. Appl Math Model, 2010, 34: 3631–3641

    MathSciNet  MATH  Google Scholar 

  49. Tang Y. Terminal sliding mode control for rigid robots. Automatica, 1998, 34: 51–56

    MathSciNet  MATH  Google Scholar 

  50. Matsumoto T, Chua L, Komuro M. The double scroll. IEEE Trans Circ Syst, 1985, 32: 797–818

    MathSciNet  MATH  Google Scholar 

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Acknowledgements

This work was jointly supported by National Natural Science Foundation of China (Grant Nos. 61673078, 61833005), Bowang Scholar Program of Chongqing Normal University, and Chongqing Natural Science Foundation (Grant No. cstc2018jcyjAX0369).

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Correspondence to Xinsong Yang or Jinde Cao.

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Xiong, X., Yang, X., Cao, J. et al. Finite-time control for a class of hybrid systems via quantized intermittent control. Sci. China Inf. Sci. 63, 192201 (2020). https://doi.org/10.1007/s11432-018-2727-5

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  • DOI: https://doi.org/10.1007/s11432-018-2727-5

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