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Self-discipline predictive control against large-scale packet dropouts using input delay approach

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  • Hong-Tao Sun
  • Chen Peng
  • Cheng Tan

Abstract

This paper develops a novel self-discipline predictive control (SPC) scheme to compensate the missing control inputs of networked control systems (NCS) under arbitrary bounded packet dropouts. Since no feedback measurements are available when there are packet dropouts, the key idea of SPC scheme is that one can adjust its controller gains only based on the latest received state measurement rather than waiting the next available measurement. Then, the future controller gains are predicted by using input delay approach while input to state stability (ISS) is arrived under Lypunov–Krasovskii method and switched system framework. In what follows, the SPC scheme based on the predicted controller gains are used to update the control inputs during packet dropout intervals. A main advantage of this work lies in that the proposed SPC scheme realises a self-stabilisation with only limited feedback measurements under large-scale packet dropouts. At last, simulations on path following control of autonomous vehicles are carried out to show the validity of the proposed SPC scheme.

Suggested Citation

  • Hong-Tao Sun & Chen Peng & Cheng Tan, 2022. "Self-discipline predictive control against large-scale packet dropouts using input delay approach," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(5), pages 934-947, April.
    • Handle: RePEc:taf:tsysxx:v:53:y:2022:i:5:p:934-947
    DOI: 10.1080/00207721.2021.1979685
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