Low-order SISO controller tuning methods for the H2, H and μ objective functions

Daniel E. Rivera, Manfred Morari

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

A methodology for synthesizing low-order compensators is outlined that explicitly accounts for model uncertainty, allows on-line controller adjustment, and is computationally simple. The method consists of applying the Internal Model Control (IMC) design procedure to a control-relevant reduced-order model; that is, a model obtained by incorporating features of the closed-loop problem as weights in the reduction procedure. As a consequence, lower-order yet better performing controllers, as compared to those resulting from equivalent methods, are obtained. The computational algorithm is outlined, and it is shown that the model reduction problem can be solved efficiently through standard linear or quadratic programming algorithms, while only the IMC filter parameters and process deadtime need to be obtained through more elaborate search techniques. The benefits of the proposed algorithm are shown through examples.

Original languageEnglish (US)
Pages (from-to)361-369
Number of pages9
JournalAutomatica
Volume26
Issue number2
DOIs
StatePublished - Mar 1990
Externally publishedYes

Keywords

  • Model reduction
  • optimal control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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