A quantitative feedback solution to the multivariable tracking error problem

  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: 2013

Volumen: 24

Número: 16

Páginas: 2331-2346

Tipo: Artículo

DOI: 10.1002/RNC.2991 SCOPUS: 2-s2.0-84912027089 WoS: WOS:000343996200010 GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: International Journal of Robust and Nonlinear Control

Resumen

This paper introduces a novel solution for the multi-input multi-output (MIMO) quantitative feedback theory control design problem with tracking error specifications. Looking for a minimum controller overdesign, the technique finds new controller quantitative feedback theory bounds based on necessary and sufficient conditions for the existence of suitable associated prefilter matrix elements. It improves previous approaches to the subject and includes (i) the possibility of a free selection of the nominal plant, (ii) a less conservative application of the Schwartz inequality to decisively reduce the potential controller overdesign, (iii) a methodology to design independently the elements of the prefilter matrix, and (iv) a scope of application to both sequential and nonsequential MIMO controller design methods. The benefits of the new control design technique are illustrated by means of two examples. The first one, a standard 2×2 MIMO problem, is provided for comparison purposes with previous approaches. The second example, included as a major control challenge, deals with a well-known demanding distillation column benchmark problem. © 2013 John Wiley & Sons, Ltd.