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Decentralised output-feedback control for a class of large-scale stochastic high-order upper-triangular nonlinear systems

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  • Liang Liu
  • Yifan Zhang

Abstract

Under the weaker conditions on the drift and diffusion terms, this paper focuses on the global decentralised output-feedback control for a class of large-scale stochastic high-order upper-triangular nonlinear systems. By introducing an appropriate coordinate transformation, the original system is transformed into an equivalent one with tunable gain. After that, by reasonably combing the homogeneous domination approach with stochastic nonlinear systems stability criterion, and skillfully choosing the low gain scale, the decentralised output-feedback controller is constructed for each subsystem to ensure that the closed-loop system is globally asymptotically stable in probability. The simulation example is given to demonstrate the effectiveness of the proposed design scheme.

Suggested Citation

  • Liang Liu & Yifan Zhang, 2017. "Decentralised output-feedback control for a class of large-scale stochastic high-order upper-triangular nonlinear systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(4), pages 838-848, March.
    • Handle: RePEc:taf:tsysxx:v:48:y:2017:i:4:p:838-848
    DOI: 10.1080/00207721.2016.1216202
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    References listed on IDEAS

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    1. Ali Koshkouei & Keith Burnham, 2011. "Adaptive backstepping sliding mode control for feedforward uncertain systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(12), pages 1935-1946.
    2. Fangzheng Gao & Yuqiang Wu & Xin Yu, 2016. "Global state feedback stabilisation of stochastic high-order nonlinear systems with high-order and low-order nonlinearities," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(16), pages 3846-3856, December.
    3. Jian Wu & Weisheng Chen & Qiguang Miao, 2013. "Asymptotic stabilisation for a class of feedforward input-delay systems with ratios of odd integers," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(11), pages 1983-1993.
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