Research article

Non-fragile sampled-data control for synchronizing Markov jump Lur'e systems with time-variant delay

  • Received: 16 March 2024 Revised: 15 July 2024 Accepted: 23 July 2024 Published: 26 July 2024
  • The issue of non-fragile sampled-data control for synchronizing Markov jump Lur'e systems (MJLSs) with time-variant delay was investigated. The time-variant delay allowed for uncertainty that was constrained to an interval with defined upper and lower boundaries. The components of the nonlinear function within the MJLSs were considered to satisfy either Lipschitz continuity or non-decreasing monotonicity. Numerically tractable conditions that ensured stochastic synchronization with a predefined $ \mathcal{L}_{2}-\mathcal{L}_{\infty} $ disturbance attenuation level for the drive-response MJLSs were established, utilizing time-dependent two-sided loop Lyapunov-Krasovskii functionals, together with integral and matrix inequalities. An exact mathematical expression of the desired controller gains can be obtained based on these conditions. Finally, an example with numerical simulation was employed to demonstrate the effectiveness of the proposed control strategies.

    Citation: Dandan Zuo, Wansheng Wang, Lulu Zhang, Jing Han, Ling Chen. Non-fragile sampled-data control for synchronizing Markov jump Lur'e systems with time-variant delay[J]. Electronic Research Archive, 2024, 32(7): 4632-4658. doi: 10.3934/era.2024211

    Related Papers:

  • The issue of non-fragile sampled-data control for synchronizing Markov jump Lur'e systems (MJLSs) with time-variant delay was investigated. The time-variant delay allowed for uncertainty that was constrained to an interval with defined upper and lower boundaries. The components of the nonlinear function within the MJLSs were considered to satisfy either Lipschitz continuity or non-decreasing monotonicity. Numerically tractable conditions that ensured stochastic synchronization with a predefined $ \mathcal{L}_{2}-\mathcal{L}_{\infty} $ disturbance attenuation level for the drive-response MJLSs were established, utilizing time-dependent two-sided loop Lyapunov-Krasovskii functionals, together with integral and matrix inequalities. An exact mathematical expression of the desired controller gains can be obtained based on these conditions. Finally, an example with numerical simulation was employed to demonstrate the effectiveness of the proposed control strategies.



    加载中


    [1] U. Parlitz, L. O. Chua, L. Kocarev, K. S. Halle, A. Shang, Transmission of digital signals by chaotic synchronization, Int. J. Bifurcation Chaos, 2 (1992), 973–977. https://doi.org/10.1142/S0218127492000562 doi: 10.1142/S0218127492000562
    [2] L. Kocarev, U. Parlitz, General approach for chaotic synchronization with applications to communication, Phys. Rev. Lett., 74 (1995), 5028. https://doi.org/10.1103/PhysRevLett.74.5028 doi: 10.1103/PhysRevLett.74.5028
    [3] Q. Xie, G. Chen, E. M. Bollt, Hybrid chaos synchronization and its application in information processing, Math. Comput. Modell., 35 (2002), 145–163. https://doi.org/10.1016/S0895-7177(01)00157-1 doi: 10.1016/S0895-7177(01)00157-1
    [4] X. Liao, P. Yu, Absolute Stability of Nonlinear Control Systems, Springer-Verlag, New York, 2008. https://doi.org/10.1007/978-1-4020-8482-9
    [5] L. M. Pecora, T. L. Carroll, Synchronization in chaotic systems, Phys. Rev. Lett., 64 (1990), 821. https://doi.org/10.1103/PhysRevLett.64.821 doi: 10.1103/PhysRevLett.64.821
    [6] Z. Tang, J. H. Park, Y. Wang, J. Feng, Distributed impulsive quasi-synchronization of Lur'e networks with proportional delay, IEEE Trans. Cybern., 49 (2019), 3105–3115. https://doi.org/10.1109/TCYB.2018.2839178 doi: 10.1109/TCYB.2018.2839178
    [7] D. Xuan, Z. Tang, J. Feng, J. H. Park, Cluster synchronization of nonlinearly coupled Lur'e networks: Delayed impulsive adaptive control protocols, Chaos, Solitons Fractals, 152 (2021), 111337. https://doi.org/10.1016/j.chaos.2021.111337 doi: 10.1016/j.chaos.2021.111337
    [8] S. Shao, J. Cao, Y. Hu, X. Liu. Prespecified-time distributed synchronization of Lur'e networks with smooth controllers, Asian J. Control, 24 (2022), 125–136. https://doi.org/10.1002/asjc.2422 doi: 10.1002/asjc.2422
    [9] J. Yang, J. Huang, X. He, W. Yang, Bipartite synchronization of Lur'e network with signed graphs based on intermittent control, ISA Trans., 135 (2023), 290–298. https://doi.org/10.1016/j.isatra.2022.10.002 doi: 10.1016/j.isatra.2022.10.002
    [10] R. Kavikumar, R. Sakthivel, O. M. Kwon, B. Kaviarasan, Reliable non-fragile memory state feedback controller design for fuzzy Markov jump systems, Nonlinear Anal. Hybrid Syst., 35 (2020), 100828. https://doi.org/10.1016/j.nahs.2019.100828 doi: 10.1016/j.nahs.2019.100828
    [11] H. Ji, Y. Li, X. Ding, J. Lu, Stability analysis of boolean networks with Markov jump disturbances and their application in apoptosis networks, Electron. Res. Arch., 30 (2022), 3422–3434. https://doi.org/10.3934/era.2022174 doi: 10.3934/era.2022174
    [12] R. Sakthivel, H. Divya, A. Parivallal, V. T. Suveetha, Quantized fault detection filter design for networked control system with Markov jump parameters, Circuits Syst. Signal Process., 40 (2021), 4741–4758. https://doi.org/10.1007/s00034-021-01693-x doi: 10.1007/s00034-021-01693-x
    [13] H. Liu, J. Cheng, J. Cao, I. Katib, Preassigned-time synchronization for complex-valued memristive neural networks with reaction–diffusion terms and Markov parameters, Neural Networks, 169 (2024), 520–531. https://doi.org/10.1016/j.neunet.2023.11.011 doi: 10.1016/j.neunet.2023.11.011
    [14] X. Zhou, S. Zhong, Delay-range-dependent exponential synchronization of Lur'e systems with Markovian switching, Int. J. Math. Comput. Sci., 4 (2010), 407–412.
    [15] J. Zhou, B. Zhang, Master-slave synchronization of singular Lur'e time-delay systems with Markovian jumping parameters, in 2020 7th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS), Guangzhou, China, (2020), 164–169. https://doi.org/10.1109/ICCSS52145.2020.9336877
    [16] X. Huang, Y. Zhou, M. Fang, J. Zhou, S. Arik, Finite-time $\mathcal{H}_\infty$ synchronization of semi-Markov jump Lur'e systems, Mod. Phys. Lett. B, 35 (2021), 2150168. https://doi.org/10.1142/S0217984921501682 doi: 10.1142/S0217984921501682
    [17] J. Zhou, J. Dong, S. Xu, Asynchronous dissipative control of discrete-time fuzzy Markov jump systems with dynamic state and input quantization, IEEE Trans. Fuzzy Syst., 31 (2023), 3906–3920. https://doi.org/10.1109/TFUZZ.2023.3271348 doi: 10.1109/TFUZZ.2023.3271348
    [18] X. Li, X. Qin, Z. Wan, W. Tai, Chaos synchronization of stochastic time-delay Lur'e systems: An asynchronous and adaptive event-triggered control approach, Electron. Res. Arch., 31 (2023), 5589–5608. https://doi.org/10.3934/era.2023284 doi: 10.3934/era.2023284
    [19] S. Santra, M. Joby, M. Sathishkumar, S. M. Anthoni, LMI approach-based sampled-data control for uncertain systems with actuator saturation: application to multi-machine power system, Nonlinear Dyn., 107 (2022), 967–982. https://doi.org/10.1007/s11071-021-06995-y doi: 10.1007/s11071-021-06995-y
    [20] Y. Zhou, X. Chang, W. Huang, Z. Li, Quantized extended dissipative synchronization for semi-Markov switching Lur'e systems with time delay under deception attacks, Commun. Nonlinear Sci. Numer. Simul., 117 (2023), 106972. https://doi.org/10.1016/j.cnsns.2022.106972 doi: 10.1016/j.cnsns.2022.106972
    [21] Q. Li, X. Liu, Q. Zhu, S. Zhong, J. Cheng, Stochastic synchronization of semi-Markovian jump chaotic Lur'e with packet dropouts subject to multiple sampling periods, J. Franklin Inst., 356 (2019), 6899–6925. https://doi.org/10.1016/j.jfranklin.2019.06.005 doi: 10.1016/j.jfranklin.2019.06.005
    [22] T. Yang, Z. Wang, X. Huang, J. Xia, Sampled-data exponential synchronization of Markovian jump chaotic Lur'e systems with multiple time delays, Chaos, Solitons Fractals, 160 (2022), 112252. https://doi.org/10.1016/j.chaos.2022.112252 doi: 10.1016/j.chaos.2022.112252
    [23] C. Ge, X. Liu, Y. Liu, C. Hua, Synchronization of inertial neural networks with unbounded delays via sampled-data control, IEEE Trans. Neural Networks Learn. Syst., 35 (2024), 5891–5901. https://doi.org/10.1109/TNNLS.2022.3222861 doi: 10.1109/TNNLS.2022.3222861
    [24] Y. Ni, Z. Wang, X. Huang, Q. Ma, H. Shen, Intermittent sampled-data control for local stabilization of neural networks subject to actuator saturation: A work-interval-dependent functional approach, IEEE Trans. Neural Networks Learn. Syst., 35 (2024), 1087–1097. https://doi.org/10.1109/TNNLS.2022.3180076 doi: 10.1109/TNNLS.2022.3180076
    [25] Y. Liu, Y. Zhang, L. Liu, S. Tong, C. L. P. Chen, Adaptive finite-time control for half-vehicle active suspension systems with uncertain dynamics, IEEE/ASME Trans. Mechatron., 26 (2021), 168–178. https://doi.org/10.1109/TMECH.2020.3008216 doi: 10.1109/TMECH.2020.3008216
    [26] Y. Wang, C. Hua, P Shi, Improved admissibility criteria for Takagi-Sugeno fuzzy singular systems with time-varying delay, IEEE Trans. Fuzzy Syst., 31 (2023), 2966–2974. https://doi.org/10.1109/TFUZZ.2023.3240250 doi: 10.1109/TFUZZ.2023.3240250
    [27] G. Yang, X. Guo, W. Che, W. Guan, Linear Systems: Non-Fragile Control and Filtering, CRC Press, 2013. https://doi.org/10.1201/b14766
    [28] X. Chang, G. Yang, Nonfragile $\mathcal{H}_\infty$ filter design for T–S fuzzy systems in standard form, IEEE Trans. Ind. Electron., 61 (2014), 3448–3458. https://doi.org/10.1109/TIE.2013.2278955 doi: 10.1109/TIE.2013.2278955
    [29] K. Liu, A. Seuret, Y. Xia, Stability analysis of systems with time-varying delays via the second-order Bessel–Legendre inequality, Automatica, 76 (2017), 138–142. https://doi.org/10.1016/j.automatica.2016.11.001 doi: 10.1016/j.automatica.2016.11.001
    [30] W. Tai, D. Zuo, J. Han, J. Zhou, Fuzzy resilient control for synchronizing chaotic systems with time-variant delay and external disturbance, Int. J. Mod. Phys. B, 35 (2021), 2150177. https://doi.org/10.1142/S0217979221501770 doi: 10.1142/S0217979221501770
    [31] N. T. T. Huyen, M. V. Thuan, N. T. Thanh, T. N. Binh, Guaranteed cost control of fractional-order switched systems with mixed time-varying delays, Comput. Appl. Math., 42 (2023), 370. https://doi.org/10.1007/s40314-023-02505-5 doi: 10.1007/s40314-023-02505-5
    [32] M. Sathishkumar, R. Sakthivel, C. Wang, B. Kaviarasan, S. M. Anthoni, Non-fragile filtering for singular Markovian jump systems with missing measurements, Signal Process., 142 (2018), 125–136. https://doi.org/10.1016/j.sigpro.2017.07.012 doi: 10.1016/j.sigpro.2017.07.012
    [33] X. Qin, J. Dong, X. Zhang, T. Jiang, J. Zhou, $\mathcal{H}_\infty$ control of time-delayed Markov jump systems subject to mismatched modes and interval conditional probabilities, Arab. J. Sci. Eng., 49 (2024), 7471–7486. https://doi.org/10.1007/s13369-023-08332-4 doi: 10.1007/s13369-023-08332-4
    [34] D. Tong, B. Ma, Q. Chen, Y. Wei, P. Shi, Finite-time synchronization and energy consumption prediction for multilayer fractional-order networks, IEEE Trans. Circuits Syst. II Express Briefs, 70 (2023), 2176–2180. https://doi.org/10.1109/TCSII.2022.3233420 doi: 10.1109/TCSII.2022.3233420
    [35] L. Yao, Z. Wang, X. Huang, Y. Li, Q. Ma, H. Shen, Stochastic sampled-data exponential synchronization of Markovian jump neural networks with time-varying delays, IEEE Trans. Neural Networks Learn. Syst., 34 (2023), 909–920. https://doi.org/10.1109/TNNLS.2021.3103958 doi: 10.1109/TNNLS.2021.3103958
    [36] G. Yang, D. Tong, Q. Chen, W. Zhou, Fixed-time synchronization and energy consumption for Kuramoto-oscillator networks with multilayer distributed control, IEEE Trans. Circuits Syst. II Express Briefs, 70 (2023), 1555–1559. https://doi.org/10.1109/TCSII.2022.3221477 doi: 10.1109/TCSII.2022.3221477
    [37] L. Shanmugam, Y. H. Joo, Design of interval type-2 fuzzy-based sampled-data controller for nonlinear systems using novel fuzzy Lyapunov functional and its application to PMSM, IEEE Trans. Syst. Man Cybern.: Syst., 51 (2021), 542–551. https://doi.org/10.1109/TSMC.2018.2875098 doi: 10.1109/TSMC.2018.2875098
    [38] M. Sathishkumar, R. Sakthivel, F. Alzahrani, B. Kaviarasan, Y. Ren, Mixed $\mathcal{H}_\infty$ and passivity-based resilient controller for nonhomogeneous Markov jump systems, Nonlinear Anal. Hybrid Syst., 31 (2019), 86–99. https://doi.org/10.1016/j.nahs.2018.08.003 doi: 10.1016/j.nahs.2018.08.003
    [39] X. Jiang, G. Xia, Z. Feng, T. Li, Non-fragile $\mathcal{H}_{\infty}$ consensus tracking of nonlinear multi-agent systems with switching topologies and transmission delay via sampled-data control, Inf. Sci., 509 (2020), 210–226. https://doi.org/10.1016/j.ins.2019.08.078 doi: 10.1016/j.ins.2019.08.078
    [40] Z. Yan, D. Zuo, T. Guo, J. Zhou, Quantized $\mathcal{H}_\infty$ stabilization for delayed memristive neural networks, Neural Comput. Appl., 35 (2023), 16473–16486. https://doi.org/10.1007/s00521-023-08510-3 doi: 10.1007/s00521-023-08510-3
    [41] T. H. Lee, J. H. Park, Improved criteria for sampled-data synchronization of chaotic Lur'e systems using two new approaches, Nonlinear Anal. Hybrid Syst., 24 (2017), 132–145. https://doi.org/10.1016/j.nahs.2016.11.006 doi: 10.1016/j.nahs.2016.11.006
    [42] W. Tai, D. Zuo, Z. Xuan, J. Zhou, Z. Wang, Non-fragile $\mathcal{L}_2-\mathcal{L}_\infty$ filtering for a class of switched neural networks, Math. Comput. Simul., 185 (2021), 629–645. https://doi.org/10.1016/j.matcom.2021.01.014 doi: 10.1016/j.matcom.2021.01.014
    [43] J. Zhou, X. Ma, Z. Yan, S. Arik, Non-fragile output-feedback control for time-delay neural networks with persistent dwell time switching: A system mode and time scheduler dual-dependent design, Neural Networks, 169 (2024), 733–743. https://doi.org/10.1016/j.neunet.2023.11.007 doi: 10.1016/j.neunet.2023.11.007
    [44] G. Chen, J. Xia, J. H. Park, H. Shen, G. Zhuang, Sampled-data synchronization of stochastic Markovian jump neural networks with time-varying delay, IEEE Trans. Neural Networks Learn. Syst., 33 (2022), 3829–3841. https://doi.org/10.1109/TNNLS.2021.3054615 doi: 10.1109/TNNLS.2021.3054615
    [45] D. A. Wilson, Convolution and Hankel operator norms for linear systems, IEEE Trans. Autom. Control, 34 (1989), 94–97. https://doi.org/10.1109/9.8655 doi: 10.1109/9.8655
    [46] A. Seuret, F. Gouaisbaut, Hierarchy of LMI conditions for the stability analysis of time-delay systems, Syst. Control Lett., 81 (2015), 1–7. https://doi.org/10.1016/j.sysconle.2015.03.007 doi: 10.1016/j.sysconle.2015.03.007
    [47] H. Zeng, Y. He, M. Wu, J. She, New results on stability analysis for systems with discrete distributed delay, Automatica, 60 (2015), 189–192. https://doi.org/10.1016/j.automatica.2015.07.017 doi: 10.1016/j.automatica.2015.07.017
    [48] A. Seuret, K. Liu, F. Gouaisbaut, Generalized reciprocally convex combination lemmas and its application to time-delay systems, Automatica, 95 (2018), 488–493. https://doi.org/10.1016/j.automatica.2018.06.017 doi: 10.1016/j.automatica.2018.06.017
    [49] K. Zhou, P. P. Khargonekar, Robust stabilization of linear systems with norm-bounded time-varying uncertainty, Syst. Control Lett., 10 (1988), 17–20. https://doi.org/10.1016/0167-6911(88)90034-5 doi: 10.1016/0167-6911(88)90034-5
    [50] S. Boyd, L. El. Ghaoui, E. Feron, V. Balakrishnan, Linear Matrix Inequalities in System and Control Theory, SIAM, Philadelphia, PA, USA, 1994. https://doi.org/10.1137/1.9781611970777
    [51] M. Wu, Y. He, J. She, Stability Analysis and Robust Control of Time-Delay Systems, Springer, New York, 2010. https://doi.org/10.1007/978-3-642-03037-6
  • Reader Comments
  • © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(391) PDF downloads(26) Cited by(0)

Article outline

Figures and Tables

Figures(7)  /  Tables(1)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog