A motor's simulated output hugs the data from one step test. It is tempting to announce that the model is accurate. But a model that was tuned on that exact trace has not yet predicted anything new.
Fit and validation are separate jobs
System identification starts from known inputs and measured outputs, selects a model family and estimates parameters. Validation then checks independent data, ideally under conditions relevant to control. A simple step may expose static gain and dominant time scale, but it may not distinguish electrical and mechanical constants uniquely, especially with noise and limited bandwidth.
Keep a load pulse or a second target out of the fitting stage. Predict it using the chosen model, then compare output and required input. A model can be adequate for one controller decision without matching every microscopic transient; state the intended use and the error that matters.
What this lab demonstrates—and what it does not
EIGENROOM does not yet fit a model to imported hardware measurements. Instead, its nominal motor is the design model and the adjustable inertia and friction multipliers change the actual simulated motor. Pin the nominal run, double actual inertia and hold the controller fixed. The nominal Bode plot and proportional root locus remain unchanged; the time response may move. That difference is the point of the exercise.
This controlled mismatch can teach why validation matters, but it is not evidence that our simulated motor represents your real device. Real hardware requires measured input/output data, unit checks, safety limits and an independent validation experiment.
Reserve at least one experiment the model has never seen. Predict that run before calling the model useful for control.