오프라인 주파수 응답 추정

Simulink^® 모델의 주파수 응답 추정, 주파수 영역 특성 검토, 선형화 검증

Simulink Control Design™에는 모델을 수정하지 않고도 Simulink에서 모델링된 시스템의 주파수 응답을 추정할 수 있는 명령줄 툴과 그래픽 모델 선형기 앱이 있습니다. 추정된 응답을 사용하여 엄밀한 선형화 결과를 검증하거나 선형 모델 동특성을 분석하거나 모수적 모델을 추정할 수 있습니다. 주파수 응답 추정에 대한 자세한 내용은 Frequency Response Estimation Basics 항목을 참조하십시오.

주파수 응답 추정은 관심 주파수에서 모델을 가진시키기 위해 선형화 입력 점에서의 입력 신호를 필요로 합니다. 자세한 내용은 Estimation Input Signals 항목을 참조하십시오.

그래픽 툴

모델 선형기	Simulink 모델 선형화
선형화 관리자	Manage linear analysis points and block linearizations

함수

모두 확장

주파수 응답 추정

추정

`frestimate`	Frequency response estimation of Simulink models
`frestimateOptions`	Options for frequency response estimation

입력 신호

`frest.Sinestream`	Input signal containing series of sine waves
`frest.createFixedTsSinestream`	Sinestream input signal with fixed sample time
`frest.Chirp`	Swept-frequency cosine input signal
`frest.PRBS`	Pseudorandom binary sequence input signal (R2020a 이후)
`frest.Random`	랜덤 입력 신호
`frest.createStep`	계단 입력 신호 만들기

시뮬레이션과 분석

`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

시변 소스와 경로 종속성

`frest.findSources`	Identify time-varying source blocks
`frest.findDepend`	List of model path dependencies

검사

Identify time-varying source blocks interfering with frequency response estimation

도움말 항목

주파수 응답 추정 기본 사항

Frequency Response Estimation Basics

A frequency response describes the steady-state response of a system to sinusoidal inputs. Simulink Control Design lets you estimate the frequency response of a model or perform online estimation of a physical plant.
Analyze Estimated Frequency Response
When you perform frequency response estimation, you can analyze the result by examining the raw simulated response and the FFT used to convert it to an estimated frequency response.

추정 입력 신호

Estimation Input Signals

For frequency response estimation, the software injects an input signal and measures the response. You can use predefined signal types such as sinestream or chirp signals, or create an arbitrary input signal.
- Sinestream Input Signals
- Chirp Input Signals
- PRBS Input Signals
- Modify Estimation Input Signals

잡음과 시변 입력

Disable Noise Sources During Frequency Response Estimation
Noise sources can interfere with the signals at the linearization output points and produce inaccurate estimation results.
Signal Processing Toolbox를 사용해 잡음이 있는 주파수 응답 모델 추정하기
윈도우와 평균화 기능을 포함하는 Signal Processing Toolbox™를 사용하여 주파수 응답 모델을 추정할 수 있습니다.
System Identification Toolbox를 사용해 잡음이 있는 주파수 응답 모델 추정하기
System Identification Toolbox™를 사용하여 주파수 응답 모델을 추정할 수 있습니다.
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.

선형화 검증

Validate Linearization in Frequency Domain Using Model Linearizer
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 Frequency Domain at Command Line
You can assess the accuracy of your linearization results at the command line by estimating the frequency response of the nonlinear model.
Validate Linearization in Time Domain
You can assess the accuracy of your linearization results by comparing the simulated output of the nonlinear model and the linearized model.

코드 생성

Generate MATLAB Code for Repeated or Batch Frequency Response Estimation
Generate MATLAB^® scripts or functions for frequency response estimation using the Model Linearizer.

문제 해결

Managing Estimation Speed and Memory

Improve frequency response estimation performance by reducing estimation time and memory requirements.
- Speed Up Frequency Response Estimation Using Parallel Computing
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.