IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v411y2021ics0096300321005816.html
   My bibliography  Save this article

Dissipative filtering for singular Markovian jump systems with generally hybrid transition rates

Author

Listed:
  • Tian, Yufeng
  • Wang, Zhanshan

Abstract

This paper studies the dissipative filtering of singular Markovian jump systems (SMJSs) with generally hybrid transition rates (GHTRs). The transition rates of the mode jumps are considered to be generally hybrid, which relax the traditional assumption in Markov jump systems that estimate errors must be completely symmetric. The introduced generally hybrid transition rates (GHTRs) make these systems more general and realistic. In order to deal with the GHTRs, a new approach named double-boundary approach is proposed. Then, a new integral inequality named Wirtinger-type free-matrix-based integral inequality (WFMII) is proposed to estimate Lyapunov-Krasovskii functional (LKF), in which some delay-product-type matrices are produced to fully link the relationship among time-varying delay and system states. Based on these ingredients, an explicit expression of the desired filter can be given to ensure the filtering error system to be stochastically admissible and strictly dissipative. The further examination to demonstrate the feasibility of the presented method is given by designing a filter of a two-loop circuit network.

Suggested Citation

  • Tian, Yufeng & Wang, Zhanshan, 2021. "Dissipative filtering for singular Markovian jump systems with generally hybrid transition rates," Applied Mathematics and Computation, Elsevier, vol. 411(C).
  • Handle: RePEc:eee:apmaco:v:411:y:2021:i:c:s0096300321005816
    DOI: 10.1016/j.amc.2021.126492
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300321005816
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2021.126492?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jin, Zhenghong & Wang, Zhanxiu, 2021. "Input-to-state stability of the nonlinear singular systems via small-gain theorem," Applied Mathematics and Computation, Elsevier, vol. 402(C).
    2. Li, Zhi-Min & Chang, Xiao-Heng & Yu, Lu, 2016. "Robust quantized H∞ filtering for discrete-time uncertain systems with packet dropouts," Applied Mathematics and Computation, Elsevier, vol. 275(C), pages 361-371.
    3. Sakthivel, R. & Suveetha, V.T. & Nithya, V. & Sakthivel, R., 2021. "Finite-time reliable filtering for Takagi–Sugeno fuzzy semi-Markovian jump systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 185(C), pages 403-418.
    4. Tan, Guoqiang & Wang, Zhanshan & Li, Cong, 2020. "H∞ performance state estimation of delayed static neural networks based on an improved proportional-integral estimator," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    5. Nithya, V. & Sakthivel, R. & Sakthivel, R. & Alzahrani, Faris, 2020. "Dissipative-based non-fragile filtering for fuzzy networked control systems with switching communication channels," Applied Mathematics and Computation, Elsevier, vol. 373(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Ning & Qi, Wenhai & Pang, Guocheng & Cheng, Jun & Shi, Kaibo, 2022. "Observer-based sliding mode control for fuzzy stochastic switching systems with deception attacks," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    2. Kwon, W. & Jin, Yongsik & Lee, S.M., 2020. "PI-type event-triggered H∞ filter for networked T-S fuzzy systems using affine matched membership function approach," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    3. Nakamori, Seiichi, 2018. "Least-squares finite impulse response fixed-lag smoother and filter in linear discrete-time stochastic systems," Applied Mathematics and Computation, Elsevier, vol. 334(C), pages 94-106.
    4. Hamdi, Issam El & Vargas, Alessandro N. & Bouzahir, Hassane & Oliveira, Ricardo C.L.F. & Acho, Leonardo, 2021. "Robust stability of stochastic systems with varying delays: Application to RLC circuit with intermittent closed-loop," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    5. Min, Huifang & Xu, Shengyuan & Yu, Xin & Fei, Shumin & Cui, Guozeng, 2020. "Adaptive Tracking Control for Stochastic Nonlinear Systems with Full-State Constraints and Unknown Covariance Noise," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    6. Yang, Yi & Chen, Fei & Lang, Jiahong & Chen, Xiangyong & Wang, Jing, 2021. "Sliding mode control of persistent dwell-time switched systems with random data dropouts," Applied Mathematics and Computation, Elsevier, vol. 400(C).
    7. Chang, Xiao-Heng & Li, Zhi-Min & Xiong, Jun & Wang, Yi-Ming, 2017. "LMI approaches to input and output quantized feedback stabilization of linear systems," Applied Mathematics and Computation, Elsevier, vol. 315(C), pages 162-175.
    8. Song, Xinmin & Duan, Zhenhua & Park, Ju H., 2016. "Linear optimal estimation for discrete-time systems with measurement-delay and packet dropping," Applied Mathematics and Computation, Elsevier, vol. 284(C), pages 115-124.
    9. Mahmoud, Magdi S. & Almutairi, Naif B., 2016. "Feedback fuzzy control for quantized networked systems with random delays," Applied Mathematics and Computation, Elsevier, vol. 290(C), pages 80-97.
    10. Lu, Jianquan & Guo, Xing & Huang, Tingwen & Wang, Zhen, 2019. "Consensus of signed networked multi-agent systems with nonlinear coupling and communication delays," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 153-162.
    11. Xiong, Shixun & Chen, Mou & Wu, Qianxian, 2019. "Predictive control for networked switch flight system with packet dropout," Applied Mathematics and Computation, Elsevier, vol. 354(C), pages 444-459.
    12. Chen, Siya & Feng, Jianwen & Wang, Jingyi & Zhao, Yi, 2020. "Almost sure exponential synchronization of drive-response stochastic memristive neural networks," Applied Mathematics and Computation, Elsevier, vol. 383(C).
    13. Dong, Zeyu & Wang, Xin & Zhang, Xian, 2020. "A nonsingular M-matrix-based global exponential stability analysis of higher-order delayed discrete-time Cohen–Grossberg neural networks," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    14. Xie, Jiyang & Zhu, Shuqian & Zhang, Dawei, 2022. "A robust distributed secure interval observation approach for uncertain discrete-time positive systems under deception attacks," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    15. Xu, Xiaozeng & Zhang, Hongbin & Zheng, Qunxian & Chen, Wei, 2022. "Global exponential stability and H∞ control of limit cycle for switched affine systems under time-dependent switching signal," Applied Mathematics and Computation, Elsevier, vol. 423(C).
    16. Yu Yao & Guodong Zhang & Yan Li, 2023. "Fixed/Preassigned-Time Stabilization for Complex-Valued Inertial Neural Networks with Distributed Delays: A Non-Separation Approach," Mathematics, MDPI, vol. 11(10), pages 1-17, May.
    17. Ju, Yanhao & Sun, Yuangong & Meng, Fanwei, 2020. "Stabilization of switched positive system with impulse and marginally stable subsystems: A mode-dependent dwell time method," Applied Mathematics and Computation, Elsevier, vol. 383(C).
    18. Shi, Xuanxuan & Shen, Mouquan, 2019. "A new approach to feedback feed-forward iterative learning control with random packet dropouts," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 399-412.
    19. Fu, Haijing & Li, Jiahui & Han, Fei & Hou, Nan & Dong, Hongli, 2021. "Outlier-resistant bserver-based H∞ PID control under stochastic communication protocol," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    20. Sakthivel, Ramalingam & Sakthivel, Rathinasamy & Kwon, Oh-Min & Selvaraj, Palanisamy, 2021. "Disturbance rejection for singular semi-Markov jump neural networks with input saturation," Applied Mathematics and Computation, Elsevier, vol. 407(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:411:y:2021:i:c:s0096300321005816. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.