Quantitative feedback control for multivariable model matching and disturbance rejection

  1. Elso, J. 1
  2. Gil-Martinez, M. 3
  3. Garcia-Sanz, M. 2
  1. 1 Universidad Pública de Navarra
    info

    Universidad Pública de Navarra

    Pamplona, España

    ROR https://ror.org/02z0cah89

  2. 2 Case Western Reserve University
    info

    Case Western Reserve University

    Cleveland, Estados Unidos

    ROR https://ror.org/051fd9666

  3. 3 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

Revista:
International Journal of Robust and Nonlinear Control

ISSN: 1049-8923

Año de publicación: 2017

Volumen: 27

Número: 1

Páginas: 121-134

Tipo: Artículo

DOI: 10.1002/RNC.3563 SCOPUS: 2-s2.0-84971349393 WoS: WOS:000389846400008 GOOGLE SCHOLAR

Otras publicaciones en: International Journal of Robust and Nonlinear Control

Resumen

This article extends two recent contributions in the field of quantitative feedback theory to the multivariable case. They concern the model matching and the measured disturbance rejection problems. The model matching problem is a tracking control problem with specifications given as acceptable deviations from an ideal response. The measured disturbance rejection problem balances feedback and feedforward actions to reject disturbances. Both perspectives present advantages over classical quantitative feedback theory techniques in certain situations. This paper develops the necessary tools to solve both control problems in the case of multi-input multi-output plants. In particular, it shows how to derive nonconservative controller bounds for each of the single-input single-output control problems in which the overall multivariable problem is divided. The result is a systematic controller design methodology for multi-input multi-output plants with structured uncertainty. The application of the technique to the well-known quadruple-tank process illustrates the benefits of the method. © 2016 John Wiley & Sons, Ltd.