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Abstracted Models for Scheduling of Event-Triggered Control Data Traffic

Part of the Lecture Notes in Control and Information Sciences book series (LNCIS,volume 475)

Abstract

Event-Triggered control (ETC) implementations have been proposed to overcome the inefficiencies of periodic (time-triggered) controller designs, namely the over-exploitation of the computing and communication infrastructure. However, the potential of aperiodic Event-Triggered techniques to reuse the freed bandwidth, and to reduce energy consumption on wireless settings, has not yet been truly reached. The main limitation to fully exploit ETC’s great traffic reductions lies on the difficulty to predict the occurrence of controller updates, forcing the use of conservative scheduling approaches in practice. Having a model of the timing behaviour of ETC is of paramount importance to enable the construction of model-based schedulers for such systems. Furthermore, on wireless control systems these schedulers allow to tightly schedule listening times, thus reducing energy consumption. In this chapter we describe an approach to model ETC traffic employing ideas from the symbolic abstractions literature. The resulting models of traffic are timed-automata. We also discuss briefly how these models can be employed to automatically synthesize schedulers.

Keywords

  • Event-triggered Control (ETC)
  • Schedule-based Models
  • Updated Account
  • Symbolic Abstraction
  • Timed Automata

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Correspondence to M. Mazo Jr. .

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Mazo Jr., M., Sharifi-Kolarijani, A., Adzkiya, D., Hop, C. (2018). Abstracted Models for Scheduling of Event-Triggered Control Data Traffic. In: Tarbouriech, S., Girard, A., Hetel, L. (eds) Control Subject to Computational and Communication Constraints. Lecture Notes in Control and Information Sciences, vol 475. Springer, Cham. https://doi.org/10.1007/978-3-319-78449-6_10

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  • DOI: https://doi.org/10.1007/978-3-319-78449-6_10

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