Structure simplification of dynamic process models

A. Leitold, K. Hangos, Z. Tuza

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Lumped process models derived from first engineering principles are usually too detailed for control purposes where only the major dynamic characteristics of the system should be captured. Two common steps of simplifying dynamic process models, the steady-state variable removal and the variable lumping simplification steps are investigated in this paper, in order to show if they preserve the key properties: The structural controllability, observability and stability of the models. In order to enable the formal analysis, these simplification steps are represented as context sensitive graph transformations acting on the structure graphs of the dynamic process models. It is shown that the simplification transformations above preserve the structural controllability and observability of process models. But only the steady-state variable removal transformation has been found not to destroy their structural stability. The variable lumping structure simplification transformation is further specialized to the case of cascade process models. It is shown that the inverse of this transformation does exist in this case, and both transformations preserve structural controllability and observability.

Original languageEnglish
Pages (from-to)69-83
Number of pages15
JournalJournal of Process Control
Volume12
Issue number1
DOIs
Publication statusPublished - Jan 2002

Fingerprint

Dynamic Process
Process Model
Simplification
Dynamic Model
Observability
Controllability
Structural Stability
Graph Transformation
Formal Analysis
Dynamic Characteristics
Cascade
Engineering
Graph in graph theory

Keywords

  • Graph
  • Model simplification
  • Model structure
  • Process control

ASJC Scopus subject areas

  • Process Chemistry and Technology
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

Cite this

Structure simplification of dynamic process models. / Leitold, A.; Hangos, K.; Tuza, Z.

In: Journal of Process Control, Vol. 12, No. 1, 01.2002, p. 69-83.

Research output: Contribution to journalArticle

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