Controllers as filters: Noise-driven swing-up control based on Maxwell's demon

Emmanouil Tzorakoleftherakis, Todd D. Murphey

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

8 Scopus citations

Abstract

In this paper we show in simulation that if the controller and the filter are combined into a single computational unit operating like a Maxwell's demon, controller-filtered noise can successfully control a system of interest. Using this method, we perform Monte Carlo tests for the swing-up control of the cart pendulum, acrobot and pendubot systems. Results show that filtered noise can indeed act as a swing-up controller, leading these systems to configurations where a locally stabilizing controller can complete the stabilization process. Potential applications of this work include the development of reliable, never-failing human-machine interfaces for rehabilitation, training and skill evaluation.

Original languageEnglish (US)
Title of host publication54rd IEEE Conference on Decision and Control,CDC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4368-4374
Number of pages7
ISBN (Electronic)9781479978861
DOIs
StatePublished - Feb 8 2015
Event54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan
Duration: Dec 15 2015Dec 18 2015

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume54rd IEEE Conference on Decision and Control,CDC 2015
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Other

Other54th IEEE Conference on Decision and Control, CDC 2015
Country/TerritoryJapan
CityOsaka
Period12/15/1512/18/15

Funding

This material is based upon work supported by the National Science Foundation under Grant CNS 1329891. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

ASJC Scopus subject areas

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

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