Parametric robust control by quantitative feedback theory

  • Osita Nwokah
  • Suhada Jayasuriya
  • Yossi Chait
Conference paper
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 170)


The problem of performance robustness, especially in the face of significant parametric uncertainty, has been increasingly recognized as a predominant issue of engineering significance in many design applications. Quantitative feedback theory (QFT) is very effective for dealing with this class of problems even when there exist hard constraints on closed loop response. In this paper, SISO-QFT is viewed formally as a sensitivity constrained multi objective optimization problem which can be used to set up a constrained H minimization problem whose solution provides an initial guess at the QFT solution. In contrast to the more recent robust control methods where phase uncertainty information is often neglected, the direct use of parametric uncertainty and phase information in QFT results in a significant reduction in the cost of feedback. An example involving a standard problem is included for completeness.


Parametric uncertainty QFT robust control 

List of Symbols Used


Banach space of essentially bounded Baire functions


Banach space of bounded analytic functions


Banach space of bounded analytic functions with elements from the ring of stable, proper real rational functions

Unit of RH

An element of RH whose inverse ∈ RH


relative degree of transfer function


single input, single output


multi-input, multi-output


radian frequency


compact parameter space with elements α


Quantitative Feedback Theory


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Copyright information

© Springer-Verlag 1992

Authors and Affiliations

  • Osita Nwokah
    • 1
  • Suhada Jayasuriya
    • 2
  • Yossi Chait
    • 3
  1. 1.School of Mechanical EngineeringPurdue UniversityWest Lafayette
  2. 2.Department of Mechanical EngineeringTexas A&M UniversityCollege Station
  3. 3.Department of Mechanical EngineeringUniversity of MassachusettsAmherst

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