Abstract
In this paper, we propose a methodology for the modeling of linear parameter-varying systems which is based on an innovative interpolation approach at the transfer function level with scaling coefficients. This interpolation approach is different from standard interpolation of state-space matrices for the modeling of linear parameter-varying systems. The proposed method starts from a discrete set of frequency-domain data samples of the system transfer function for fixed values of the scheduling parameters. Then, a rational system identification step is used to generate the root macromodels. Finally, an innovative interpolation approach at the transfer function level with scaling coefficients is used to build the linear parameter-varying representation. Pertinent numerical results validate the proposed linear parameter-varying modeling technique.
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