Realization-preserving structure and order reduction of nonlinear energetic system models using energy trajectory correlations

Tulga Ersal, Hosam K. Fathy, Jeffrey L. Stein

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Previous work by the authors developed algorithms for simplifying the structure of a lumped dynamic system model and reducing its order. This paper extends this previous work to enable simultaneous model structure and order reduction. Specifically, it introduces a new energy-based metric to evaluate the relative importance of energetic connections in a model. This metric (1) accounts for correlations between energy flow patterns in a model using the Karhunen-Loève expansion; (2) examines all energetic connections in a model, thereby assessing the relative importance of both energetic components and their interactions, and enabling both order and structural reduction; and (3) is realization preserving, in the sense of not requiring a state transformation. A reduction scheme based on this metric is presented and illustrated using a simple example. The example shows that the proposed method can successfully concurrently reduce model order and structure without requiring a realization change, and that it can provide an improved assessment of the importance of various model components due to its correlation-based nature.

Original languageEnglish (US)
Pages (from-to)1-8
Number of pages8
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Volume131
Issue number3
DOIs
StatePublished - May 2009

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Mechanical Engineering
  • Computer Science Applications

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