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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.

Apps

System Identification Identify models of dynamic systems from measured data

Functions

idnlarx Nonlinear ARX model
nlarx Estimate parameters of nonlinear ARX model
nlarxOptions Option set for nlarx
isnlarx Detect nonlinearity in estimation data
init Set or randomize initial parameter values
getpvec Model parameters and associated uncertainty data
setpvec Modify value of model parameters
polyreg Powers and products of standard regressors
customreg Custom regressor for nonlinear ARX models
addreg Add custom regressors to nonlinear ARX model
getreg Regressor expressions and numerical values in nonlinear ARX model
customnet Custom nonlinearity estimator for nonlinear ARX and Hammerstein-Wiener models
linear Class representing linear nonlinearity estimator for nonlinear ARX models
neuralnet Class representing neural network nonlinearity estimator for nonlinear ARX models
treepartition Class representing binary-tree nonlinearity estimator for nonlinear ARX models
wavenet Create a wavelet network nonlinearity estimator object
sigmoidnet Class representing sigmoid network nonlinearity estimator for nonlinear ARX and Hammerstein-Wiener models
evaluate Value of nonlinearity estimator at given input
sim Simulate response of identified model
simOptions Option set for sim
predict Predict K-step ahead model output
predictOptions Option set for predict
compare Compare model output and measured output
compareOptions Option set for compare
forecast Forecast identified model output
forecastOptions Option set for forecast
plot Plot nonlinearity of nonlinear ARX model
evaluate Value of nonlinearity estimator at given input
getDelayInfo Get input/output delay information for idnlarx model structure
findop Compute operating point for Nonlinear ARX model
findopOptions Option set for findop
operspec Construct operating point specification object for idnlarx model
linearize Linearize nonlinear ARX model
linapp Linear approximation of nonlinear ARX and Hammerstein-Wiener models for given input

Blocks

IDNLARX Model Simulate nonlinear ARX model in Simulink software
IDDATA Sink Export iddata object to MATLAB workspace
IDDATA Source Import iddata object from MATLAB workspace

Topics

What are Nonlinear ARX Models?

Understand the structure of a nonlinear ARX model.

Available Nonlinearity Estimators 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.

Validating 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.

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