哈默斯坦-维纳模型

线性动态系统与饱和度和死区等静态非线性之间的关联

使用哈默斯坦-维纳模型来估计原本是线性系统的静态非线性。您可以使用哈默斯坦-维纳结构来捕获影响线性系统输入和输出的传感器和作动器中的物理非线性效应，例如死区和饱和度。要估计哈默斯坦-维纳模型，请使用系统辨识或 nlhw 函数。

App

系统辨识从测量数据辨识动态系统模型

函数

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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 (自 R2025a 起)
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) (自 R2021b 起)
idNeuralNetworkMultilayer neural network mapping function for nonlinear ARX models and Hammerstein-Wiener models (requires Statistics and Machine Learning Toolbox or Deep Learning Toolbox) (自 R2023b 起)
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
compare将辨识模型输出与测量的输出进行比较
compareOptionsOption set for compare
nlhwPlotPlot input and output nonlinearity, and linear responses of Hammerstein-Wiener model (自 R2023a 起)
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

模块

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Hammerstein-Wiener ModelSimulate Hammerstein-Wiener model in Simulink software
Iddata Sink将仿真数据作为 iddata 对象导出到 MATLAB 工作区
Iddata SourceImport time-domain data stored in iddata object in MATLAB workspace

主题

精选示例

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.