Regressor expressions and numerical values in nonlinear ARX model
Rs = getreg(model)
Rm = getreg(model,data)
Rm = getreg(model,data,init)
Rm = getreg(___,'Type',regressorType)
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 wavenet
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.
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 in
data
. When the iddata
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 to
max(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
Rm
timetable
of regressor values for all or a specified
subset of regressors. Each column in Rm
contains as many
rows as there are data samples. For a model with nr
regressors, Rm
contains one column for each regressor.
When data
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 signal u1
by two time
samples. Similarly, the expression 'y2(t-1)'
computes the
regressor by delaying the output signal y2
by one time
sample.
The order of regressors in Rs
corresponds to regressor
indices in the idnlarx
object property
model.RegressorUsage
.
customRegressor
| evaluate
| idnlarx
| linearRegressor
| polynomialRegressor