Robust quantised control of hybrid stochastic systems based on discrete-time state and mode observations

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Song, Gongfei and Mao, Xuerong and Li, Tao (2019) Robust quantised control of hybrid stochastic systems based on discrete-time state and mode observations. International Journal of Control, 92 (8). pp. 1836-1845. ISSN 0020-7179 (https://doi.org/10.1080/00207179.2017.1414310)

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Abstract

In this paper, the problems of robust quantized feedback control are studied for hybrid stochastic systems based on discrete-time observations of state and mode. All of the existing results in this area design the quantized feedback control based on continuous observations of the state and mode for all time t ≥ 0 (see [23–25]). This is the first paper where we propose to use the quantized feedback control based on discrete-time observations of the state and mode. The key reason for this is to reduce the burden of communication by using not only the quantization (i.e. in the direction of state axis), but also discrete-time observations of state and mode (i.e. in the direction of time axis). Thus, the designed quantized feedback controllers have to be based on the discrete-time observations of state and mode. Clearly, the new quantized feedback controllers are more realistic and cost less in practice. Two examples with computer simulations will be provided to illustrate the effectiveness of the proposed control method.

ORCID iDs

Song, Gongfei, Mao, Xuerong ORCID logoORCID: https://orcid.org/0000-0002-6768-9864 and Li, Tao;
  • Item type:Article
    ID code:62534
    Dates:
    Date
    Event
    3 August 2019
    Published
    27 December 2017
    Published Online
    5 December 2017
    Accepted
    29 May 2017
    Submitted
    Notes:© Informa UK Limited, trading as Taylor & Francis Group Song, G., Mao, X., & Li, T. (2017). Robust quantised control of hybrid stochastic systems based on discrete-time state and mode observations. International Journal of Control, 92(8), 1836–1845. https://doi.org/10.1080/00207179.2017.1414310
    Subjects:Science > Mathematics > Electronic computers. Computer science
    Department:Faculty of Science > Mathematics and Statistics
    Depositing user: Pure Administrator
    Date deposited:06 Dec 2017 11:05
    Last modified:11 Nov 2024 11:51
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/62534
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