The Adaptive Frequency Sweep () study and study step are used, for example, to compute the response of a linear or linearized model subjected to harmonic excitation for several frequencies with a fine frequency resolution using a reduced-order model in the frequency domain. The Asymptotic Waveform Evaluation (AWE) model reduction is performed by a moment matching technique where Padé approximation or a Taylor series expansion is used for the transfer function in a specified frequency interval. This study step corresponds to an AWE Solver.

Specify the frequencies to use for the frequency sweep. Select the unit to use from the Frequency unit list (default: Hz). Enter the frequencies in the Frequencies field using space-separated numbers or the range function.

Use the Asymptotic Waveform Evaluation (AWE) Expressions table to specify a list of globally available scalar-valued expressions to be used for error estimation by the AWE algorithm.

In the AWE algorithm, the values of the expressions specified in the Asymptotic Waveform Evaluation (AWE) Expressions table in the Study Settings section are evaluated at one or more points of a parameter interval using certain expansions. The AWE algorithm is considered to have converged in that interval if the functional values resulting from the different expansions and evaluation points are similar enough. Use the Relative tolerance field to specify to what relative tolerance the functional values must agree at the evaluation points.