periodicRegressor
Specify periodic regressor for nonlinear ARX model
Description
Periodic regressors are sine and cosine functions of delayed input and output
variables. For example, sin(y(t–1)) and
cos(y(t–1)) are both periodic regressors with delays
of one sample. A periodicRegressor
object encapsulates a set of periodic
regressors. Use periodicRegressor
objects when you create nonlinear ARX
models using idnlarx
or nlarx
. You can specify periodicRegressor
objects along with
linearRegressor
,
polynomialRegressor
,
and customRegressor
objects and combine them into a single combined regressor set.
Creation
Syntax
Description
creates a scReg
= periodicRegressor(Variables,Lags)periodicRegressor
object that contains sine and cosine
functions for each output and input variable in Variables
and the corresponding lags in Lags
. For example, if Variables
contains
{'y','u'}
and Lags
contains the corresponding
lag vector {1,2}
, then the function creates the regressors
sin(y(t-1)),
cos(y(t-1)),
sin(u(t-2)), and
cos(u(t-2)).
applies the frequency multiplier scReg
= periodicRegressor(Variables,Lags,W)W
to each formula. For example, if Variables
contains
{'y','u'}
, Lags
contains
{1,2}
, and W
is equal to 1.5
,
then the function creates the regressors
sin(1.5y(t-1)),
cos(1.5y(t-1)),
sin(1.5u(t-2)), and
cos(1.5u(t-2)).
approximates each regressor signal as a Fourier series that contains scReg
= periodicRegressor(Variables,Lags,W,NumTerms)NumTerms
coefficients by creating NumTerms
periodic
regressors for each lagged variable, as shown in the sequence sin(x),
sin(2x), …, sin(Mx),
cos(x), cos(2x), …,
cos(Mx).
In this sequence, x represents a lagged variable, such as
y(t-1), and M is equal to
NumTerms
.
specifies whether to apply absolute value operations that create regressors such as
|sin(y(t-k))| or
|cos(u(t))|.scReg
= periodicRegressor(Variables,Lags,W,NumTerms,UseAbsolute
)
Input Arguments
Properties
Examples
Version History
Introduced in R2022a
See Also
idnlarx
| nlarx
| getreg
| linearRegressor
| polynomialRegressor
| customRegressor