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Finite-Time Control for Markov Jump Systems with Partly Known Transition Probabilities and Time-Varying Polytopic Uncertainties

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Advances in Neural Networks – ISNN 2015 (ISNN 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9377))

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Abstract

In this paper, the finite-time control problem for Markov systems with partly known transition probabilities and polytopic uncertainties is investigated. The main result provided is a sufficient conditions for finite-time stabilization via state feedback controller, and a simpler case without controller is also considered, based on switched quadratic Lyapunov function approach. All conditions are shown in the form of LMIs. An illustrative example is presented to demonstrate the result.

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Author information

Authors and Affiliations

  1. School of Science, Jiangnan University, Wuxi, 214122, China

    Chen Zheng, Xiaozheng Fan, Manfeng Hu, Yongqing Yang & Yinghua Jin

  2. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, 214122, China

    Manfeng Hu, Yongqing Yang & Yinghua Jin

Authors
  1. Chen Zheng
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  2. Xiaozheng Fan
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  3. Manfeng Hu
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  4. Yongqing Yang
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  5. Yinghua Jin
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Corresponding author

Correspondence to Chen Zheng .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Xiaolin Hu

  2. Fuzhou University, Fuzhou, China

    Yousheng Xia

  3. School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China

    Yunong Zhang

  4. Chinese Academy of Sciences, Institute of Automation, Beijing, China

    Dongbin Zhao

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© 2015 Springer International Publishing Switzerland

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Zheng, C., Fan, X., Hu, M., Yang, Y., Jin, Y. (2015). Finite-Time Control for Markov Jump Systems with Partly Known Transition Probabilities and Time-Varying Polytopic Uncertainties. In: Hu, X., Xia, Y., Zhang, Y., Zhao, D. (eds) Advances in Neural Networks – ISNN 2015. ISNN 2015. Lecture Notes in Computer Science(), vol 9377. Springer, Cham. https://doi.org/10.1007/978-3-319-25393-0_2

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  • DOI: https://doi.org/10.1007/978-3-319-25393-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25392-3

  • Online ISBN: 978-3-319-25393-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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