Periodic event-triggered control for nonlinear networked control systems

Wei Wang (Corresponding author), Romain Postoyan, Dragan Nesic, W.P.M.H. Heemels

Research output: Contribution to journalArticleAcademicpeer-review

15 Citations (Scopus)

Abstract

Periodic event-triggered control (PETC) is an appealing paradigm for the implementation of controllers on platforms with limited communication resources, a typical example being networked control systems. In PETC, transmissions over the communication channel are triggered by an event generator, which depends solely on the available plant and controller data and is only evaluated at given sampling instants to enable its digital implementation. In this paper, we consider the general scenario, where the controller communicates with the plant via multiple decoupled networks. Each network may contain multiple nodes, in which case a dedicated protocol is used to schedule transmissions among these nodes. The transmission instants over the networks are asynchronous and generated by local event generators. At given sampling instants, the local event generator evaluates a rule, which only involves the measurements and the control inputs available locally, to decide whether a transmission is needed over the considered network. Following the emulation approach, we show how to design local triggering generators to ensure input-to-state stability and Lp stability for the overall system based on a continuous-time output-feedback controller that robustly stabilizes the network-free system. The method is applied to a class of Lipschitz nonlinear systems, for which we formulate the design conditions as linear matrix inequalities. The effectiveness of the scheme is illustrated via simulations of a nonlinear example.

Original languageEnglish
Article number8703764
Pages (from-to)620-635
Number of pages16
JournalIEEE Transactions on Automatic Control
Volume65
Issue number2
DOIs
Publication statusPublished - Feb 2020

Keywords

  • Lyapunov methods
  • networked control systems
  • nonlinear control systems
  • robust stability

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