Identifiability Issues for Parameter - Varying Andmultidimensional Linear Systems

نویسندگان

  • Lawton H. Lee
  • Kameshwar Poolla
چکیده

This paper considers the identiiability of state space models for a system that is expressed as a linear fractional transformation (LFT): a constant matrix (containing identiied parameters) in feedback with a nite-dimensional, block-diagonal (\structured") linear operator. This model structure can represent linear time-invariant, linear parameter-varying, uncertain, and multidimensional systems. Families of input-output equivalent realizations are characterized as manifolds in the parameter space whose tangent spaces|and orthogonal complements|can be obtained via singular value decomposition. As illustrated by a numerical example, restricting iterative parameter estimation algorithms (e.g., maximum-likelihood with nonlinear programming) to the orthogonal directions ooers signiicant computational advantages.

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تاریخ انتشار 1997