Performance prediction in uncertain networked control systems using ℒ1-adaptation-based distributed event-triggering

Xiaofeng Wang, Naira Hovakimyan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper studies networked control systems in the presence of communication constraints and uncertainties. We propose an ℒ1- adaption-based distributed event-triggering broadcast scheme, where ℒ1 adaptive controller is embedded in each subsystem. In this scheme, a subsystem broadcasts its state information to its neighbors when its local error exceeds a constant. We compare the resulting system with an ideal model that has perfect communication and no uncertainties. Performance bounds on these two system are derived. A trade-off is established among the performance bounds, the event thresholds, the adaptation rates, and the bandwidths of the lowpass filters in the ℒ1 adaptation structure. With this scheme, the prediction of the performance of the networked control systems in the presence of uncertainties can be significantly improved. This is important for safety-critical applications.

Original languageEnglish (US)
Title of host publication2010 49th IEEE Conference on Decision and Control, CDC 2010
Pages7570-7575
Number of pages6
DOIs
StatePublished - Dec 1 2010
Event2010 49th IEEE Conference on Decision and Control, CDC 2010 - Atlanta, GA, United States
Duration: Dec 15 2010Dec 17 2010

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other2010 49th IEEE Conference on Decision and Control, CDC 2010
CountryUnited States
CityAtlanta, GA
Period12/15/1012/17/10

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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    Wang, X., & Hovakimyan, N. (2010). Performance prediction in uncertain networked control systems using ℒ1-adaptation-based distributed event-triggering. In 2010 49th IEEE Conference on Decision and Control, CDC 2010 (pp. 7570-7575). [5717265] (Proceedings of the IEEE Conference on Decision and Control). https://doi.org/10.1109/CDC.2010.5717265