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Sliding mode control for networked control systems: A brief survey.

Weixiang Zhou1, Yueying Wang2, Yinzheng Liang3

  • 1College of Information Engineering, Shanghai Maritime University, Shanghai 201306, PR China.

ISA Transactions
|January 16, 2021
PubMed
Summary

This review explores sliding mode control (SMC) for networked control systems (NCSs), detailing its application to address packet dropouts, time delays, and signal quantization challenges in NCSs.

Keywords:
Networked constraintsNetworked control systemsPacket dropoutsSignal quantizationSliding mode controlTime delays

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Area of Science:

  • Control Engineering
  • Networked Systems
  • Nonlinear Control Theory

Background:

  • Networked control systems (NCSs) integrate control systems with communication networks, presenting unique challenges.
  • Advanced control theories increasingly incorporate network functionalities into system design.
  • Sliding mode control (SMC) offers inherent robustness for nonlinear systems with uncertainties.

Purpose of the Study:

  • To provide a comprehensive review of recent advancements in sliding mode control (SMC) for networked control systems (NCSs).
  • To summarize essential technical constraints and challenges in applying SMC to NCSs.
  • To discuss potential future research directions in this domain.

Main Methods:

  • Review of existing literature on SMC applied to NCSs.
  • Analysis of SMC strategies addressing packet dropouts, time delays, and signal quantization.
  • Summarization of key theoretical and practical considerations for SMC in NCSs.

Main Results:

  • SMC is an effective method for handling uncertainties and nonlinearities in NCSs.
  • Detailed results are presented for SMC application under constraints like packet dropouts, time delays, and signal quantization.
  • The review highlights the robustness of SMC on the sliding mode surface.

Conclusions:

  • Sliding mode control is a powerful tool for robust control in networked environments.
  • Further research is needed to address emerging challenges and optimize SMC for complex NCSs.
  • The paper identifies promising future research avenues for SMC in NCSs.