User`s guide

4 Nonlinear Black-Box Model Identification
Next Steps After Estimating Nonlinear Black-Box Models
After estimating nonlinear black-box models, you can perform the following
operations:
• View parameter values, standard deviations of the parameters, loss
function, and Akaike’s Final Prediction Error (FPE) Criterion at the
command line using the
present command or by get the EstimationInfo
property of the model.
• Simulate the model using the
sim command.
• Predict the model output using the
predict command.
• Compute linear approximation of nonlinear ARX and Hammerstein-Wiener
models using
linearize or linapp. lineari ze prov ides a first-order
Taylor series approximation of the system about an operation point (also
called tangent linearization).
linapp computes a linear a ppro ximation of
a nonline ar model for a given input. For more information about these
commands, see the “Computing Linear Approximations of Nonlinear
Black-Box Models” on page 4-33.
• Import identified m o d e ls into Simulink soft ware for simula tio n . For more
information, see Chapter 11, “Using System Identification Toolbox Blocks”.
After computing a linear approxim ation of a nonlinear model, you can perform
linear an alysis and control design on your model using Con trol System
Toolbox comm ands. For more information, see “Using Mode ls with Control
System Toolbox Software” on page 10-2.
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