Continuous-Time Identification using LQG-Balanced Model Reduction

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingResearchpeer-review


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.
Original languageEnglish
Title of host publicationProceedings of the 15th IFAC world congress
ISBN (Print)0-08-044184X
Publication statusPublished - 2002

Subject classification (UKÄ)

  • Control Engineering


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