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Hammerstein-Wiener 모델

포화, 불감대와 같은 정적 비선형성을 선형 동적 시스템에 연결

정적 비선형성을 제외하면 선형 시스템이 되는 시스템에서 Hammerstein-Wiener 모델로 정적 비선형성을 추정합니다. 이들 모델은 툴박스에서 idnlhw 객체로 표현됩니다. System Identification 앱 또는 명령줄에서 nlhw 명령을 사용하여 Hammerstein-Wiener 모델을 추정할 수 있습니다.

System Identification측정된 데이터에서 동적 시스템의 모델 식별하기

함수

모두 확장

idnlhwHammerstein-Wiener model
nlhwEstimate Hammerstein-Wiener model
nlhwOptionsOption set for nlhw
initSet or randomize initial parameter values
getpvecObtain model parameters and associated uncertainty data
setpvecModify values of model parameters
customnetCustom network function for nonlinear ARX and Hammerstein-Wiener models
deadzoneCreate a dead-zone nonlinearity estimator object
poly1dClass representing single-variable polynomial nonlinear estimator for Hammerstein-Wiener models
pwlinearCreate a piecewise-linear nonlinearity estimator object
saturationCreate a saturation nonlinearity estimator object
sigmoidnetSigmoid network function for nonlinear ARX and Hammerstein-Wiener models
unitgainSpecify absence of nonlinearities for specific input or output channels in Hammerstein-Wiener models
wavenetWavelet network function for nonlinear ARX and Hammerstein-Wiener models
evaluateValue of nonlinearity estimator at given input
simSimulate response of identified model
simOptionsOption set for sim
compareCompare identified model output and measured output
compareOptionsOption set for compare
plotPlot input and output nonlinearity, and linear responses of Hammerstein-Wiener model
evaluateValue of nonlinearity estimator at given input
findopCompute operating point for Hammerstein-Wiener model
findopOptionsOption set for findop
operspecConstruct operating point specification object for idnlhw model
linearizeLinearize Hammerstein-Wiener model
linappLinear approximation of nonlinear ARX and Hammerstein-Wiener models for given input

블록

모두 확장

Hammerstein-Wiener ModelSimulate Hammerstein-Wiener model in Simulink software
Iddata Sink시뮬레이션 데이터를 iddata 객체로 MATLAB 작업 영역으로 내보내기
Iddata SourceImport time-domain data stored in iddata object in MATLAB workspace

도움말 항목

What are Hammerstein-Wiener Models?

Understand the structure of Hammerstein-Wiener models.

Available Nonlinearity Estimators for Hammerstein-Wiener Models

Choose from piecewise linear, sigmoid, wavelet, saturation, dead zone, polynomial, and custom network nonlinearities.

Identifying Hammerstein-Wiener Models

Specify the Hammerstein-Wiener model structure, and configure the estimation algorithm.

Validating Hammerstein-Wiener Models

Plot model nonlinearities, analyze residuals, and simulate model output.

Using Hammerstein-Wiener Models

Simulate and predict model output, linearize Hammerstein-Wiener models, and import estimated models into the Simulink® software.

Linear Approximation of Nonlinear Black-Box Models

Choose the approach for computing linear approximations, compute operating points for linearization, and linearize your model.

How the Software Computes Hammerstein-Wiener Model Output

How the software evaluates the output of nonlinearity estimators and uses this output to compute the model response.

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