Linearly Combining Sensor Measurements Optimally to Enforce an SPR Transfer Matrix

Ryan James Caverly, James Richard Forbes

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

2 Scopus citations

Abstract

This paper presents methods to combine measurements of a linear time-invariant system in such a manner that the new system obtained is strictly positive real (SPR). In particular, this paper focuses on how to best combine measurements in a linear fashion by minimizing the difference in an H 2 or H∞ sense between the new system and a given desired system. The methods proposed to linearly combine sensor measurements rely on linear matrix inequalities (LMIs), which lead to tractable synthesis procedures. Numerical examples involving noncolocated elastic mechanical systems are provided that illustrate the effectiveness of the proposed techniques when used for output tracking control.

Original languageEnglish (US)
Title of host publication2018 IEEE Conference on Control Technology and Applications, CCTA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1289-1294
Number of pages6
ISBN (Electronic)9781538676981
DOIs
StatePublished - Oct 26 2018
Externally publishedYes
Event2nd IEEE Conference on Control Technology and Applications, CCTA 2018 - Copenhagen, Denmark
Duration: Aug 21 2018Aug 24 2018

Publication series

Name2018 IEEE Conference on Control Technology and Applications, CCTA 2018

Other

Other2nd IEEE Conference on Control Technology and Applications, CCTA 2018
CountryDenmark
CityCopenhagen
Period8/21/188/24/18

Bibliographical note

Funding Information:
This work was supported in part by the Natural Sciences and Engineering Research Council of Canada’s Postgraduate Scholarship program and National Science Foundation Award Number 1550103.

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