Tensor SVD and distributed control

Research output: Contribution to journalConference articlepeer-review

Abstract

The (approximate) diagonalization of symmetric matrices has been studied in the past in the context of distributed control of an array of collocated smart actuators and sensors. For distributed control using a two dimensional array of actuators and sensors, it is more natural to describe the system transfer function as a complex tensor rather than a complex matrix. In this paper, we study the problem of approximately diagonalizing a transfer function tensor via the tensor singular value decomposition (TSVD) for a locally spatially invariant system, and study its application along with the technique of recursive orthogonal transforms to achieve distributed control for a smart structure.

Original languageEnglish
Article number26
Pages (from-to)258-268
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5757
DOIs
StatePublished - 2005
EventSmart Structures and Materials 2005 - Modeling, Signal Processing, and Control - San Diego, CA, United States
Duration: Mar 7 2005Mar 9 2005

Keywords

  • Active Noise Suppression
  • Distributed Control
  • Recursive Orthogonal Transforms
  • Smart Structures
  • Spatial Invariance
  • Tensor Singular Value Decomposition

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