getreg
Regressor expressions and numerical values in nonlinear ARX model
Syntax
Rs = getreg(model)
Rm = getreg(model,data)
Rm = getreg(model,data,init)
Rm = getreg(___,'Type',regressorType)
Description
Rs = getreg(model)
returns expressions for computing regressors
in the nonlinear ARX model. model
is an idnlarx
object. A typical use of the regression matrices built by
getreg
is to generate input data when you want to evaluate the
output of a mapping function such as idWaveletNetwork
using evaluate
. For example, the following pair of commands evaluates the
output of a mapping function
model
.
Regressor_Value = getreg(model,data,'z')
y = evaluate(model.OutputFcn,RegressorValue)
y = predict(model,data,1,predictOptions('InitialCondition','z'))
Rm = getreg(model,data)
returns regressor values as a timetable
for the specified input/output data set
data
.
Rm = getreg(model,data,init)
uses the initial conditions that are
specified in init
. The first N
rows of each
regressor matrix depend on the initial states init
, where
N
is the maximum delay in the regressors (see
getDelayInfo
).
Rm = getreg(___,'Type',
returns the names of the regressors of the specified regressorType
)regressorType
.
For example, use the command Rm = getreg(model,'Type','input')
to
return the names of only the input regressors.
Input Arguments
data
iddata
object containing measured data or numeric matrix that contains the values of the output and input variables in the order[model.OutputName model.InputName]
.init
Initial conditions of your data:
'z'
(default) specifies zero initial state.NaN
denotes unknown initial conditions.Real column vector containing the initial state values. For more information on initial states, see Definition of idnlarx States in
idnlarx
. For multiple-experiment data, this is a matrix where each column specifies the initial state of the model corresponding to that experiment.iddata
object containing input and output samples at time instants before to the first sample indata
. When theiddata
object contains more samples than the maximum delay in the model, only the most recent samples are used. The number of samples required is equal tomax(getDelayInfo(model))
.
model
iddata
object representing nonlinear ARX model.regressorType
Type of regressor to return, specified as one of the following:
'all'
(default) — All regressors'input'
— Only input regressors'output'
— Only output regressors'standard'
— Only linear and polynomial regressors'custom'
— Only custom regressors
Output Arguments
Rm
timetable
of regressor values for all or a specified subset of regressors. Each column inRm
contains as many rows as there are data samples. For a model withnr
regressors,Rm
contains one column for each regressor. Whendata
contains multiple experiments,Rm
is a cell array where each element corresponds to a timetable of regressor values for an experiment.Rs
Regressor expressions represented as a cell array of character vectors. For example, the expression
'u1(t-2)'
computes the regressor by delaying the input signalu1
by two time samples. Similarly, the expression'y2(t-1)'
computes the regressor by delaying the output signaly2
by one time sample.The order of regressors in
Rs
corresponds to regressor indices in theidnlarx
object propertymodel.RegressorUsage
.
Examples
Version History
Introduced in R2007aSee Also
idnlarx
| linearRegressor
| polynomialRegressor
| customRegressor
| evaluate