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Nonlinear ARX Models

Nonlinear behavior modeled using dynamic networks such as sigmoid and wavelet

Use nonlinear ARX models to represent nonlinearities in your system using dynamic nonlinearity estimators such as wavelet networks, tree-partitioning, and sigmoid networks. In the toolbox, these models are represented as idnlarx objects. You can estimate Nonlinear ARX models in the System Identification app, or at the command line using the nlarx command.


System IdentificationIdentify models of dynamic systems from measured data


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idnlarxNonlinear ARX model
nlarxEstimate parameters of nonlinear ARX model
nlarxOptionsOption set for nlarx
isnlarxDetect nonlinearity in estimation data
initSet or randomize initial parameter values
getpvecObtain model parameters and associated uncertainty data
setpvecModify values of model parameters
linearRegressorSpecify linear regressor for nonlinear ARX model
polynomialRegressorSpecify polynomial regressor for nonlinear ARX model
customRegressorSpecify custom regressor for nonlinear ARX model
getregRegressor expressions and numerical values in nonlinear ARX model
polyreg(Not recommended) Powers and products of standard regressors
customreg(Not recommended) Custom regressor for nonlinear ARX models
addreg(Not recommended) Add custom regressors to nonlinear ARX model
customnetCustom network function for nonlinear ARX and Hammerstein-Wiener models
linearLinear mapping object for nonlinear ARX models
neuralnetClass representing neural network nonlinearity estimator for nonlinear ARX models
treepartitionTree-partitioned nonlinear function for nonlinear ARX models
wavenetWavelet network function for nonlinear ARX and Hammerstein-Wiener models
sigmoidnetSigmoid 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
predictPredict K-step-ahead model output
predictOptionsOption set for predict
compareCompare identified model output and measured output
compareOptionsOption set for compare
forecastForecast identified model output
forecastOptionsOption set for forecast
plotPlot nonlinearity of nonlinear ARX model
evaluateValue of nonlinearity estimator at given input
getDelayInfoGet input/output delay information for idnlarx model structure
findopCompute operating point for Nonlinear ARX model
findopOptionsOption set for findop
operspecConstruct operating point specification object for idnlarx model
linearizeLinearize nonlinear ARX model
linappLinear approximation of nonlinear ARX and Hammerstein-Wiener models for given input


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Nonlinear ARX ModelSimulate nonlinear ARX 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


What are Nonlinear ARX Models?

Understand the structure of a nonlinear ARX model.

Available Mapping Functions for Nonlinear ARX Models

Choose from sigmoid, wavelet, tree partition, linear, neural, and custom network nonlinearities.

Identifying Nonlinear ARX Models

Specify the Nonlinear ARX structure, and configure the estimation algorithm.

Validate Nonlinear ARX Models

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

Using Nonlinear ARX Models

Simulate, predict, and forecast model output, linearize nonlinear ARX 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 Nonlinear ARX Model Output

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

Featured Examples