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Frequency response estimation requires an input signal at the linearization input point to excite the model at frequencies of interest, such as a chirp or sinestream signal. A sinestream input signal is a series of sinusoids, where each sine wave excites the system for a period of time. You can inject the input signal anywhere in your model and log the simulated output, without having to modify your model.
Frequency response estimation adds the input signal you design to the existing Simulink^{®} signals at the linearization input point, and simulates the model to obtain the output at the linearization output point. For more information about supported input signals and their impact on the estimation algorithm, see Creating Input Signals for Estimation.
For multiple-input multiple-output (MIMO) systems, frequency response estimation injects the signal at each input channel separately to simulate the corresponding output signals. The estimation algorithm uses the inputs and the simulated outputs to compute the MIMO frequency response. If you want to inject different input signal at the linearization input points of a multiple-input system, treat your system as separate single-input systems. Perform independent frequency response estimations for each linearization input point using frestimate, and concatenate your frequency response results.
Frequency response estimation correctly handles open-loop linearization input and output points. For example, if the input linearization point is open, the input signal you design adds to the constant operating point value. The operating point is the initial output of the block with a loop opening.
The estimated frequency response is related to the input and output signals as:
$$G(s)\approx \frac{\text{fastFouriertransformof}{y}_{est}(t)}{\text{fastFouriertransform}{u}_{est}(t)}$$
where u_{est}(t) is the injected input signal and y_{est}(t) is the corresponding simulated output signal.