Documentation

Frequency Response Estimation

Estimate frequency response, examine frequency-domain characteristics, validate linearization

A frequency response describes the steady-state response of a system to sinusoidal inputs. Simulink® Control Design™ software has both command-line tools and a graphical Linear Analysis Tool for estimating the frequency response of your system. You can use the estimated response to validate exact linearization results, analyze linear model dynamics, or estimate parametric models. For more information about frequency response estimation, see What Is a Frequency Response Model?.

Frequency response estimation requires an input signal at the linearization input point to excite the model at the frequencies of interest. For more information, see Estimation Input Signals.

Graphical Tools

Linear Analysis Tool Linearize Simulink models

Functions

frestimate Frequency response estimation of Simulink models
frestimateOptions Options for frequency response estimation
frest.Sinestream Signal containing series of sine waves
frest.createFixedTsSinestream Sinestream input signal with fixed sample time
frest.Chirp Swept-frequency cosine signal
frest.Random Random input signal for simulation
frest.createStep Step input signal
frest.simCompare Plot time-domain simulation of nonlinear and linear models
frest.simView Plot frequency response model in time- and frequency-domain
getSimulationTime Final time of simulation for frequency response estimation
frest.findSources Identify time-varying source blocks
frest.findDepend List of model path dependencies

Topics

Frequency Response Estimation Basics

What Is a Frequency Response Model?

A frequency response describes the steady-state response of a system to sinusoidal inputs.

Model Requirements

To estimate a frequency response for your model, first disable blocks that simulate noise and blocks that generate time-varying signals.

Estimate Frequency Response Using Linear Analysis Tool

Estimate the frequency response of a Simulink model using a manually constructed sinestream input signal.

Estimate Frequency Response with Linearization-Based Input Using Linear Analysis Tool

Estimate the frequency response of a Simulink model using an input signal based on the linearization of the model.

Estimate Frequency Response at the Command Line

Estimate the frequency response of a Simulink model at the MATLAB® command line.

Analyze Estimated Frequency Response

Analyze your frequency response estimation results by simulating the estimated model.

Estimation Input Signals

Estimation Requires Input and Output Signals

To estimate a frequency response model, inject signals at linearization input points and measure the corresponding output signals.

Estimation Input Signals

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.

Create Sinestream Input Signals

Create sinestream input signals using the Linear Analysis Tool or at the command line.

Create Chirp Input Signals

Create chirp input signals using the Linear Analysis Tool or at the command line.

Modify Estimation Input Signals

When frequency response estimation produces unexpected results, you can try modifying the input signal properties.

Noise and Time-Varying Inputs

Disable Noise Sources During Frequency Response Estimation

Noise sources can interfere with the signals at the linearization output points and produce inaccurate estimation results.

Estimate Frequency Response Models with Noise Using Signal Processing Toolbox

You can also estimate a frequency response model using Signal Processing Toolbox™ software, which includes windowing and averaging.

Estimate Frequency Response Models with Noise Using System Identification Toolbox

You can also estimate a frequency response model using System Identification Toolbox™ software.

Effects of Time-Varying Source Blocks on Frequency Response Estimation

Time-varying source blocks drive the model away from the operating point of the linearized system, which prevents the response from reaching steady state.

Validation of Linearization

Validate Linearization In Frequency Domain

You can assess the accuracy of your linearization results by estimating the frequency response of the nonlinear model and comparing the result with the response of the linearized model.

Validate Linearization In Time Domain

You can assess the accuracy of your linearization results by comparing the simulated output of nonlinear model and the linearized model.

Code Generation

Generate MATLAB Code for Repeated or Batch Frequency Response Estimation

Generate MATLAB scripts or functions for frequency response estimation using the Linear Analysis Tool.

Troubleshooting

Managing Estimation Speed and Memory

Improve frequency response estimation performance by reducing estimation time and memory requirements.

Troubleshooting Frequency Response Estimation

If your estimated frequency response does not match the expected behavior of your system, you can use the time-domain and frequency-domain response plots to help improve the results.

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