Robust Stability Under Mixed Time Varying, Time Invariant and Parametric Uncertainty

Abstract

Robustness analysis is considered for systems with structured uncertainty involving a combination of linear time-invariant and linear time-varying perturbations, and parametric uncertainty. A necessary and sufficient condition for robust stability in terms of the structured singular value p is obtained, based on a finite augmentation of the original problem. The augmentation corresponds to considering the system at a fixed number of frequencies. Sufficient conditions based on scaled small-gain are also considered and characterized. A substantial amount of research in recent years has been devoted to analysis and synthesis of control systems o achieve robust stability and performance in the presence of structured uncertainty. This implies a decentralized nature of the uncertain perturbation, which is a reasonable modeling choice for complex systems, where uncertainty may be introduced at the subsystem level (see Safonov [17] and Doyle [5] for early treatments of this). In addition t o this "spatial" structure, different assumptions can be made on the dynamic properties of the uncertainty: real parametric, linear time invariant (LTI), linear time varying (LTV) or nonlinear perturbations. All these uncertainty classes arise naturally in modeling. Parametric uncertainty appears frequently in first principles models; LTI perturbations are well suited when

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1995
Accession Number
ADA464794

Entities

People

  • Fernando Paganini

Organizations

  • California Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Boundaries
  • Complex Systems
  • Computations
  • Convex Sets
  • Electrical Engineering
  • Frequency
  • Frequency Bands
  • Frequency Domain
  • Frequency Response
  • Heuristic Methods
  • Inequalities
  • Power Distribution
  • Standards
  • Steady State
  • Transfer Functions
  • Uncertainty

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Calculus or Mathematical Analysis