When you batch linearize a model, the software returns a model array containing the linearized models. There are two ways to validate a linearized model, but both methods have some computational overhead. This overhead can make validating each model in the batch linearization results infeasible. Therefore, it can be cost effective to validate either a single model or a subset of the batch linearization results. You can use linear analysis plots and commands to determine the validation candidates. For information regarding the tools that you can use for such analysis, see Linear Analysis.
You can validate a linearization using the following approaches:
Obtain a frequency response estimation of the nonlinear model, and compare its response to that of the linearized model. For an example, see Validate Linearization In Frequency Domain.
Simulate the nonlinear model and compare its time-domain response to that of the linearized model. For an example, see Validate Linearization In Time Domain.