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. Hammerstein-Wiener 구조체를 사용하여 선형 시스템의 입력 및 출력(예: 불감대 및 포화)에 영향을 미치는 센서 및 액추에이터의 물리적 비선형 효과를 캡처할 수 있습니다. Hammerstein-Wiener 모델을 추정하려면 System Identification 앱 또는 nlhw 함수를 사용하십시오.

앱

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
idCustomNetworkCustom network function for nonlinear ARX and Hammerstein-Wiener models
idDeadZoneCreate a dead-zone nonlinearity estimator object
idPolynomial1DClass representing single-variable polynomial nonlinear estimator for Hammerstein-Wiener models
idPiecewiseLinearPiecewise-linear nonlinearity estimator object
idPiecewiseConstantPiecewise-constant nonlinearity estimator object (R2025a 이후)
idSaturationCreate a saturation nonlinearity estimator object
idSigmoidNetworkSigmoid network function for nonlinear ARX and Hammerstein-Wiener models
idUnitGainSpecify absence of nonlinearities for specific input or output channels in Hammerstein-Wiener models
idWaveletNetworkWavelet network function for nonlinear ARX and Hammerstein-Wiener models
idGaussianProcessGaussian process regression mapping function for nonlinear ARX and Hammerstein-Wiener models (requires Statistics and Machine Learning Toolbox) (R2021b 이후)
idNeuralNetworkMultilayer neural network mapping function for nonlinear ARX models and Hammerstein-Wiener models (requires Statistics and Machine Learning Toolbox or Deep Learning Toolbox) (R2023b 이후)
evaluateEvaluate output values of idnlarx or idnlhw mapping object array for given set of input values
simSimulate response of identified model
simOptionsOption set for sim
compareCompare identified model output with measured output
compareOptionsOption set for compare
nlhwPlotPlot input and output nonlinearity, and linear responses of Hammerstein-Wiener model (R2023a 이후)
evaluateEvaluate output values of idnlarx or idnlhw mapping object array for given set of input values
idnlhw/findopCompute operating point for Hammerstein-Wiener model
findopOptionsOption set for findop
idnlhw/operspecConstruct operating point specification object for idnlhw model
idnlhw/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 공간으로 내보내기
Iddata SourceImport time-domain data stored in iddata object in MATLAB workspace

도움말 항목

추천 예제

A Tutorial on Identification of Nonlinear ARX and Hammerstein-Wiener Models

A Tutorial on Identification of Nonlinear ARX and Hammerstein-Wiener Models

Identify single-input-single-output (SISO) nonlinear black box models using measured input-output data.

Create Black-Box Models of a Robotic Arm System Using Neural Networks

Create Black-Box Models of a Robotic Arm System Using Neural Networks

Use neural networks as the nonlinear function when you model nonlinear ARX and Hammerstein-Wiener models. It compares the nonlinear systems estimated using different types of neural networks, activation functions, and number of layers.

Hammerstein-Wiener Model of SI Engine Torque Dynamics

Hammerstein-Wiener Model of SI Engine Torque Dynamics

Describes modeling the nonlinear torque dynamics of a spark-ignition (SI) engine as a Hammerstein-Wiener model. The identified model can be used for hardware-in-the-loop (HIL) testing, powertrain control, diagnostic, and training algorithm design. For example, you can use the model for aftertreatment control and diagnostics algorithm development. For more information on Hammerstein-Wiener models, see Hammerstein-Wiener Models.