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Robust stability and performance for interval process plants.

Balasaheb M Patre1, P J Deore

  • 1SGGS Institute of Engineering and Technology, Vishnupuri, Nanded-431 606, India. bmpatre@yahoo.com

ISA Transactions
|March 28, 2007
PubMed
Summary

This study presents a robust control design for interval plants, ensuring stability and performance despite parameter uncertainties. The method effectively addresses robust Hurwitz stability and system performance using a novel two-degrees-of-freedom approach.

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Area of Science:

  • Control Engineering
  • Systems Theory
  • Robust Control

Background:

  • Interval plants present challenges in control design due to parameter uncertainties.
  • Ensuring both robust stability and performance is critical for reliable control systems.
  • Existing methods may not adequately address the complexities of interval plant control.

Purpose of the Study:

  • To develop a two-degrees-of-freedom control design methodology for interval plants.
  • To guarantee robust stability and performance in the presence of parameter uncertainties.
  • To establish necessary and sufficient conditions for robust Hurwitz stability of interval polynomials.

Main Methods:

  • Derived necessary and sufficient conditions for robust Hurwitz stability of interval polynomials.
  • Applied these conditions to design a robust control system for a second-order unstable interval plant.
  • Incorporated a pre-filter to achieve desired system performance.

Main Results:

  • A novel control design methodology for interval plants was successfully developed.
  • The method guarantees robust stability and performance for systems with bounded parameter uncertainties.
  • Simulation results validated the efficacy of the proposed control design.

Conclusions:

  • The proposed control design methodology offers an effective solution for interval plants.
  • The established conditions for robust Hurwitz stability are crucial for practical applications.
  • This work contributes to advancing robust control design for uncertain systems.