Robustness of classifier-in-the-loop control systems: A hybrid-systems approach

Hasan A. Poonawala, Ufuk Topcu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

This paper studies continuous-state dynamical systems that use a classifier to determine the control input. Since the classifier output belongs to a finite set, the feedback control is a piece-wise constant function of the state. We therefore model the closed-loop system as a switched system. The decision surfaces of the classifier in the feature space dictate determine the switching surfaces in the state space. Therefore, the classifier affects the stability of the closed-loop system. Any analysis of the nominal closed-loop system may not be valid in states or environments that the training data for the classifier do not represent. We propose techniques to determine when the stability of the nominal system can be extended to unseen states and/or environments.

Original languageEnglish
Title of host publication2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
Pages2738-2743
Number of pages6
ISBN (Electronic)9781509028733
DOIs
StatePublished - Jun 28 2017
Event56th IEEE Annual Conference on Decision and Control, CDC 2017 - Melbourne, Australia
Duration: Dec 12 2017Dec 15 2017

Publication series

Name2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
Volume2018-January

Conference

Conference56th IEEE Annual Conference on Decision and Control, CDC 2017
Country/TerritoryAustralia
CityMelbourne
Period12/12/1712/15/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

ASJC Scopus subject areas

  • Decision Sciences (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Control and Optimization

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