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An Overview and Deep Investigation on Sampled-Data-Based Event-Triggered Control and Filtering for Networked Systems

IEEE Transactions on Industrial Informatics · 2016 · Vol. 13(1) · pp. 4–16
Xian‐Ming ZhangQing‐Long HanBao–Lin Zhang

Abstract

This paper provides an overview and makes a deep investigation on sampled-data-based event-triggered control and filtering for networked systems. Compared with some existing event-triggered and self-triggered schemes, a sampled-data-based event-triggered scheme can ensure a positive minimum inter-event time and make it possible to jointly design suitable feedback controllers and event-triggered threshold parameters. Thus, more attention has been paid to the sampled-data-based event-triggered scheme. A deep investigation is first made on the sampled-data-based event-triggered scheme. Then, recent results on sampled-data-based event-triggered state feedback control, dynamic output feedback control, H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> filtering for networked systems are surveyed and analyzed. An overview on sampled-data-based event-triggered consensus for distributed multiagent systems is given. Finally, some challenging issues are addressed to direct the future research.

Distributed Control Multi-Agent SystemsStability and Control of Uncertain SystemsNeural Networks Stability and SynchronizationEvent (particle physics)Computer scienceScheme (mathematics)Control (management)Event dataReal-time computingDistributed computingControl theory (sociology)Data miningArtificial intelligence

Funding

  • Griffith University
  • Australian Research Council
Citations
757
FWCI
79.87
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