Identification for robust multivariable control: The design of experiments

doi:10.1016/0005-1098(94)90094-9

Automatica

Volume 30, Issue 10, October 1994, Pages 1541-1554

https://doi.org/10.1016/0005-1098(94)90094-9 Get rights and content

Abstract

An approach to the design of experiments for the identification of linear MIMO models that will provide robust model-based control is presented. The design criteria, based on conditions for robust stability and performance, are developed from singluar value decompositions (SVD) characterization of structured model mismatch. The resulting designs minimize uncertainties in certain structural parameters in the SVD of the multivariable model rather than simply the magnitude of the model mismatch. An important feature of these designs is that input perturbations applied in the low-gain directions of the multivariable process have much larger magnitudes than those applied in the high-gain directions. This leads to input sequences which are neither binary nor independent. The results are used to provide an intuitive justification for performing identification under closed-loop multivariable control. Examples are presented which illustrate both the physical interpretations of the designs, and the effectiveness of using a sequential design approach.

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^☆: This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by Editor Torsten Söderström.

^‡: Current address: The M.W. Kellogg Company, Houston, TX 77210-4557, U.S.A.

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PaperIdentification for robust multivariable control: The design of experiments☆

Abstract

Chem. Eng. Sci.

Automatica

Automatica

Advances in process identification

Multivariable feedback design: concepts for a classical/modern synthesis

IEEE Trans. Aut. Control

Internal model control. 1. A unifying review and some new results

Ind. Eng. Chem. Process Des. Dev.

Internal model control. 2. Design procedure for multivariable systems

Ind. Eng. Chem. Process Des. Dev.

Connecting identification and robust control: A new challenge

Approximate identification in view of LQG feedback design

Control oriented system identification: a worst case/deterministic approach in H∞

IEEE Trans. Aut. Control

Paper
Identification for robust multivariable control: The design of experiments☆

Control oriented system identification: a worst case/deterministic approach in H_∞