Parameterization of Model Validating Sets for Uncertainty Bound OptimizationsGiven experimental data and a priori assumptions on nominal model and a linear fractional transformation uncertainty structure, feasible conditions for model validation is given. All unknown but bounded exogenous inputs are assumed to occur at the plant outputs. With the satisfaction of the feasible conditions for model validation, it is shown that a parameterization of all model validating sets of plant models is possible. The new parameterization can be used as a basis for the development of a systematic way to construct model validating uncertainty models which have specific linear fractional transformation structure for use in robust control design and analysis. The proposed feasible condition (existence) test and the parameterization is computationally attractive as compared to similar tests currently available.
Document ID
20040090516
Acquisition Source
Langley Research Center
Document Type
Other
Authors
Lim, K. B. (NASA Langley Research Center Hampton, VA, United States)
Giesy, D. P. (NASA Langley Research Center Hampton, VA, United States)