Training classifiers for feedback control

Hasan A. Poonawala, Niklas Lauffer, Ufuk Topcu

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

5 Scopus citations


One approach for feedback control using high dimensional and rich sensor measurements is to classify the measurement into one out of a finite set of situations, each situation corresponding to a (known) control action. This approach computes a control action without estimating the state. Such classifiers are typically learned from a finite amount of data using supervised machine learning algorithms. We model the closed-loop system resulting from control with feedback from classifier outputs as a piece-wise affine differential inclusion. We show how to train a linear classifier based on performance measures related to learning from data and the local stability properties of the resulting closed-loop system. The training method is based on the projected gradient descent algorithm. We demonstrate the advantage of training classifiers using control-theoretic properties on a case study involving navigation using range-based sensors.

Original languageEnglish
Title of host publication2019 American Control Conference, ACC 2019
Number of pages7
ISBN (Electronic)9781538679265
StatePublished - Jul 2019
Event2019 American Control Conference, ACC 2019 - Philadelphia, United States
Duration: Jul 10 2019Jul 12 2019

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Conference2019 American Control Conference, ACC 2019
Country/TerritoryUnited States

Bibliographical note

Funding Information:
This material is based upon work supported by the National Science Foundation under Grant No. 1646522 and Grant No. 1652113. Hasan A. Poonawala is with the Department of Mechanical Engineering, University of Kentucky, Lexington, KY 40506, USA. Niklas Lauffer is with the University of Texas, Austin, TX 78712, USA. Ufuk Topcu is with the Department of Aerospace Engineering, University of Texas, Austin, TX 78712, USA.

Publisher Copyright:
© 2019 American Automatic Control Council.

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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