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Hammerstein-Wiener Models

Connection of linear dynamic systems with static nonlinearities such as saturation and dead zone

Use Hammerstein-Wiener models to estimate static nonlinearities in an otherwise linear system. In the toolbox, these models are represented as idnlhw objects. You can estimate Hammerstein-Wiener models in the System Identification app, or at the command line using the nlhw command.

Apps

System IdentificationIdentify models of dynamic systems from measured data

Functions

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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
idPiecewiseLinearCreate a piecewise-linear nonlinearity estimator object
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) (Since R2021b)
idNeuralNetworkMultilayer neural network mapping function for nonlinear ARX models and Hammerstein-Wiener models (requires Statistics and Machine Learning Toolbox or Deep Learning Toolbox) (Since R2023b)
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 (Since R2023a)
evaluateEvaluate output values of idnlarx or idnlhw mapping object array for given set of input values
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

Blocks

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Hammerstein-Wiener ModelSimulate Hammerstein-Wiener model in Simulink software
Iddata SinkExport simulation data as iddata object to MATLAB workspace
Iddata SourceImport time-domain data stored in iddata object in MATLAB workspace

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