The quality of identified models is inherently linked to the amount of information contained in the data used for identification. After a short introduction into the topic and the presentation of the model family and identification process, general purpose test signals are discussed, some of which are manipulated in order to achieve suitable data for the identification of nonlinear dynamic TS-models. Before this contribution is concluded, a case study is presented.