Regulation of linear systems using event-based detection sensors

Prince Singh, Sze Zheng Yong, Emilio Frazzoli

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In this paper, we investigate the problem of regulating a continuous-time linear time-invariant (LTI) system to a desired point using discrete event measurements from signal change detection sensors with a logarithmic event generation threshold (trigger), which includes the recently developed neuromorphic vision sensors. Existing control algorithms typically only process periodic measurements, and thus, a new class of algorithms needs to be developed that can efficiently process the sensors' asynchronous discrete events for control tasks. Thus, we present a novel control design procedure that regulates the hybrid system, consisting of the continuous LTI system and a discrete-event signal change observation model, to a desired set point. Moreover, we provide the set of thresholds (sufficient conditions) for the given system to fulfill the regulation task. The effectiveness of our approach is illustrated on an unstable system.

Original languageEnglish (US)
Article number8500318
Pages (from-to)373-380
Number of pages8
JournalIEEE Transactions on Automatic Control
Volume64
Issue number1
DOIs
StatePublished - Jan 2019

Keywords

  • H infinity control
  • Hybrid systems
  • Robotics
  • Uncertain systems
  • Visual servo control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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