Robust control design of a single degree-of-freedom magnetic levitation system by quantitative feedback theory

Feng Tian, Mark Nagurka

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

4 Scopus citations

Abstract

A magnetic levitation (maglev) system is inherently nonlinear and open-loop unstable because of the nature of magnetic force. Most controllers for maglev systems are designed based on a nominal linearized model. System variations and uncertainties are not accommodated. The controllers are generally designed to satisfy gain and phase margin specifications, which may not guarantee a bound on the sensitivity. To address these issues, this paper proposes a robust control design method based on Quantitative Feedback Theory (QFT) applied to a single degree-of-freedom (DOF) maglev system. The controller is designed to successfully meet the stability requirement, robustness specifications, and bounds on the sensitivity. Experiments verify that the controller maintains stable levitation even with 100% load variation. Experiments prove that it guarantees the transient response design requirements even with 100% load change and 39% model uncertainties. The QFT control design method discussed in this paper can be applied to other open-loop unstable systems as well as systems with large uncertainties and variations to improve system robustness.

Original languageEnglish
Title of host publicationASME/ISCIE 2012 International Symposium on Flexible Automation, ISFA 2012
PublisherAmerican Society of Mechanical Engineers (ASME)
Pages109-115
Number of pages7
ISBN (Print)9780791845110
DOIs
StatePublished - 1 Jan 2012
Externally publishedYes
EventASME/ISCIE 2012 International Symposium on Flexible Automation, ISFA 2012 - St. Louis, MO, United States
Duration: 18 Jun 201220 Jun 2012

Publication series

NameASME/ISCIE 2012 International Symposium on Flexible Automation, ISFA 2012

Conference

ConferenceASME/ISCIE 2012 International Symposium on Flexible Automation, ISFA 2012
Country/TerritoryUnited States
CitySt. Louis, MO
Period18/06/1220/06/12

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

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