Continuous-Time Identification using LQG-Balanced Model Reduction

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Abstract

System identification of continuous-time model based on discrete-time data can be performed using a algorithm combining linear regression and LQG-balanced model reduction. The approach is applicable also to unstable system dynamics and it provides balanced models for optimal linear prediction and control.

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Subject classification (UKÄ) – MANDATORY

  • Control Engineering
Original languageEnglish
Title of host publicationProceedings of the 15th IFAC world congress
PublisherElsevier
ISBN (Print)0-08-044184X
Publication statusPublished - 2002
Publication categoryResearch
Peer-reviewedYes