Acquiring Data from a System (System Identification Toolkit)
Identifying a system involves a number of choices with regard to the system output signals you want to measure and the input signals you want to manipulate. The choices you make about how to manipulate system inputs, types of signal conditioning, signal ranges, and sampling behavior affect the validity of the model you obtain. You can use different modeling techniques on the same experimental data set. However, if the data set does not reflect the behavior of interest, you must acquire a more descriptive data set.
Because the system identification process is often an experimental process, the entire process often is time consuming and possibly costly. Therefore, you must think about the design of process prior to experimenting with various identification techniques.