IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v386y2020ics0096300320304665.html
   My bibliography  Save this article

Admissibility analysis of stochastic singular systems with Poisson switching

Author

Listed:
  • Jiao, Ticao
  • Zong, Guangdeng
  • Pang, Guochen
  • Zhang, Housheng
  • Jiang, Jishun

Abstract

This paper addresses the mean square admissibility problem for a class of stochastic singular systems with Poisson switching. By using H-representation approach, we show the equivalence between mean square admissibility and robust admissibility of a deterministic system, which is an extension of the result in the case of deterministic system [1]. Based on multiple Lyapunov functions and matrix decomposition approaches, some easily verifiable sufficient conditions without equality constraint are established and can be conveniently used to state feedback controller design. Some admissibility criteria are constructed for linear singular systems with Poisson switching. Three examples including a RLC circuit and a mass-spring-damper system are introduced to demonstrate the validity of the theoretical results.

Suggested Citation

  • Jiao, Ticao & Zong, Guangdeng & Pang, Guochen & Zhang, Housheng & Jiang, Jishun, 2020. "Admissibility analysis of stochastic singular systems with Poisson switching," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    • Handle: RePEc:eee:apmaco:v:386:y:2020:i:c:s0096300320304665
    DOI: 10.1016/j.amc.2020.125508
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300320304665
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2020.125508?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. Jiao, Shiyu & Shen, Hao & Wei, Yunliang & Huang, Xia & Wang, Zhen, 2018. "Further results on dissipativity and stability analysis of Markov jump generalized neural networks with time-varying interval delays," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 338-350.
    2. Liu, Guobao & Xu, Shengyuan & Wei, Yunliang & Qi, Zhidong & Zhang, Zhengqiang, 2018. "New insight into reachable set estimation for uncertain singular time-delay systems," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 769-780.
    3. Yan, Zhiguo & Park, Ju H. & Zhang, Weihai, 2018. "A unified framework for asymptotic and transient behavior of linear stochastic systems," Applied Mathematics and Computation, Elsevier, vol. 325(C), pages 31-40.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sergey Goolak & Viktor Tkachenko & Svitlana Sapronova & Vaidas Lukoševičius & Robertas Keršys & Rolandas Makaras & Artūras Keršys & Borys Liubarskyi, 2022. "Synthesis of the Current Controller of the Vector Control System for Asynchronous Traction Drive of Electric Locomotives," Energies, MDPI, vol. 15(7), pages 1-19, March.
    2. Chen, Wenbin & Lu, Junwei & Zhuang, Guangming & Gao, Fang & Zhang, Zhengqiang & Xu, Shengyuan, 2022. "Further results on stabilization for neutral singular Markovian jump systems with mixed interval time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 420(C).

    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. Liu, Shouqiang & Yu, Mengjing & Li, Miao & Xu, Qingzhen, 2019. "The research of virtual face based on Deep Convolutional Generative Adversarial Networks using TensorFlow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 667-680.
    2. Sun, Meng & Zhuang, Guangming & Xia, Jianwei & Wang, Yanqian & Chen, Guoliang, 2022. "Stochastic admissibility and H∞ output feedback control for singular Markov jump systems under dynamic measurement output event-triggered strategy," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    3. Jiao, Shiyu & Shen, Hao & Wei, Yunliang & Huang, Xia & Wang, Zhen, 2018. "Further results on dissipativity and stability analysis of Markov jump generalized neural networks with time-varying interval delays," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 338-350.
    4. Wang, Jing & Hu, Xiaohui & Wei, Yunliang & Wang, Zhen, 2019. "Sampled-data synchronization of semi-Markov jump complex dynamical networks subject to generalized dissipativity property," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 853-864.
    5. Xu, Bo & Liang, Yanjun & Li, Yuan-Xin & Hou, Zhongsheng, 2022. "Adaptive command filtered fixed-time control of nonlinear systems with input quantization," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    6. 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).
    7. Huang, Chengdai & Liu, Heng & Chen, Xiaoping & Cao, Jinde & Alsaedi, Ahmed, 2020. "Extended feedback and simulation strategies for a delayed fractional-order control system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    8. Dai, Mingcheng & Huang, Zhengguo & Xia, Jianwei & Meng, Bo & Wang, Jian & Shen, Hao, 2019. "Non-fragile extended dissipativity-based state feedback control for 2-D Markov jump delayed systems," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    9. Song, Bo & Zhang, Ya & Park, Ju H., 2021. "H∞ control for Poisson-driven stochastic systems," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    10. Jiao, Ticao & Park, Ju H. & Zong, Guangdeng & Liu, Jian & Chen, Yu, 2019. "Stochastic stability analysis of switched genetic regulatory networks without stable subsystems," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 261-277.
    11. Li, Feng & Song, Shuai & Zhao, Jianrong & Xu, Shengyuan & Zhang, Zhengqiang, 2019. "Synchronization control for Markov jump neural networks subject to HMM observation and partially known detection probabilities," Applied Mathematics and Computation, Elsevier, vol. 360(C), pages 1-13.
    12. Shafiya, M. & Nagamani, G. & Dafik, D., 2022. "Global synchronization of uncertain fractional-order BAM neural networks with time delay via improved fractional-order integral inequality," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 191(C), pages 168-186.
    13. Liu, Guobao & Chen, Xiangyong & Shen, Zhongyu & Liu, Yajuan & Jia, Xianglei, 2022. "Reachable set estimation for continuous delayed singularly perturbed systems with bounded disturbances," Applied Mathematics and Computation, Elsevier, vol. 416(C).
    14. Hu, Xiaohui & Xia, Jianwei & Wei, Yunliang & Meng, Bo & Shen, Hao, 2019. "Passivity-based state synchronization for semi-Markov jump coupled chaotic neural networks with randomly occurring time delays," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 32-41.
    15. Liu, Rong-Rong & Xiong, Jun & Zhang, Zaolin, 2023. "Reliable induced L∞ control for polytopic uncertain continuous-time singular systems with dynamic quantization," Applied Mathematics and Computation, Elsevier, vol. 443(C).
    16. 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).
    17. Shi, Kaibo & Wang, Jun & Zhong, Shouming & Zhang, Xiaojun & Liu, Yajuan & Cheng, Jun, 2019. "New reliable nonuniform sampling control for uncertain chaotic neural networks under Markov switching topologies," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 169-193.
    18. Li, Wenhua & Gao, Xingbao & Li, Ruoxia, 2020. "Stability and synchronization control of inertial neural networks with mixed delays," Applied Mathematics and Computation, Elsevier, vol. 367(C).
    19. Nguyen, Cuong M. & Pathirana, Pubudu N. & Trinh, Hieu, 2019. "Robust observer and observer-based control designs for discrete one-sided Lipschitz systems subject to uncertainties and disturbances," Applied Mathematics and Computation, Elsevier, vol. 353(C), pages 42-53.
    20. Li, Rongchang & Zhang, Qingling, 2018. "Robust H∞ sliding mode observer design for a class of Takagi–Sugeno fuzzy descriptor systems with time-varying delay," Applied Mathematics and Computation, Elsevier, vol. 337(C), pages 158-178.

    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:386:y:2020:i:c:s0096300320304665. 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.