Observability and controllability analysis of linear systems subject to data losses

R.M. Jungers, A. Kundu, W.P.M.H. Heemels

Research output: Contribution to journalArticleAcademicpeer-review

29 Citations (Scopus)

Abstract

We provide algorithmically verifiable necessary and sufficient conditions for fundamental system theoretic properties of discrete-time linear, systems subject to data losses. More precisely, the systems in our modeling framework are subject to disruptions (data losses) in the feedback loop, where the set of possible data loss sequences is captured by an automaton. As such, the results are applicable in the context of shared (wireless) communication networks and/or embedded architectures where some information on the data loss behavior is available a priori. We propose an algorithm for deciding observability (or the absence of it) for such systems, and show how this algorithm can be used also to decide other properties including constructibility, controllability, reachability, null-controllability, detectability, and stabilizability by means of relations that we establish among these properties. The main apparatus for our analysis is the celebrated Skolem's Theorem from Linear Algebra. Moreover, we study the relation between the model adopted in this paper and a previously introduced model where, instead of allowing dropouts in the feedback loop, one allows for time-varying delays.

Original languageEnglish
Article number8170282
Pages (from-to)3361-3376
Number of pages16
JournalIEEE Transactions on Automatic Control
Volume63
Issue number10
DOIs
Publication statusPublished - 1 Oct 2018

Keywords

  • Automata
  • Automaton
  • Constrained Switched System
  • Controllability
  • Data losses
  • Linear systems
  • Observability
  • Switched systems
  • Wireless communication
  • Wireless Control
  • data losses
  • constrained switched system
  • controllability
  • wireless control
  • observability

Fingerprint

Dive into the research topics of 'Observability and controllability analysis of linear systems subject to data losses'. Together they form a unique fingerprint.

Cite this