Retrieving structural nonlinear information using the best linear approximation

Since nonlinear (NL) identification is often very time consuming, it is highly desirable to carefully select a well suited model structure prior to the actual identification. In this study the focus is on the detection of the presence of NL feedback. Therefore, the frequency response function (FRF) of the best linear approximation (BLA) is measured at different excitation signal settings. Two properties of the excitation are varied to analyze the nonlinear behavior:
1. Amplitude (RMS value) level
2. DC level (offset or set points)
The goal of the study is to find out what is the best strategy to vary the excitation signal, in order to obtain information about the structure of the system. Two case studies will be presented on different NL-feedback systems.