step
Update model parameters and output online using recursive estimation algorithm
Description
[
updates
parameters and output of the model specified in System object™, EstimatedParameters
,EstimatedOutput
]
= step(obj
,y
,InputData
)obj
,
using measured output, y
, and input data.
step
puts the object into a locked state.
In a locked state you cannot change any nontunable properties of the
object, such as model order, data type, or estimation algorithm.
The EstimatedParameters
and InputData
depend
on the online estimation System object:
recursiveAR
—step
returns the estimated polynomial A(q) coefficients of a single output AR model using time-series output data.
[A,EstimatedOutput] = step(obj,y)
recursiveARMA
—step
returns the estimated polynomial A(q) and C(q) coefficients of a single output ARMA model using time-series output data, y.
[A,C,EstimatedOutput] = step(obj,y)
recursiveARX
—step
returns the estimated polynomial A(q) and B(q) coefficients of a SISO or MISO ARX model using measured input and output data, u and y, respectively.
[A,B,EstimatedOutput] = step(obj,y,u)
.recursiveARMAX
—step
returns the estimated polynomial A(q), B(q), and C(q) coefficients of a SISO ARMAX model using measured input and output data, u and y, respectively.
[A,B,C,EstimatedOutput] = step(obj,y,u)
.recursiveOE
—step
returns the estimated polynomial B(q), and F(q) coefficients of a SISO Output-Error polynomial model using measured input and output data, u and y, respectively.
[B,F,EstimatedOutput] = step(obj,y,u)
.recursiveBJ
—step
returns the estimated polynomial B(q), C(q), D(q), and F(q) coefficients of a SISO Box-Jenkins polynomial model using measured input and output data, u and y, respectively.
[B,C,D,F,EstimatedOutput] = step(obj,y,u)
.recursiveLS
—step
returns the estimated system parameters, θ, of a single output system that is linear in estimated parameters, using regressors H and output data y.
[theta,EstimatedOutput] = step(obj,y,H)
.
Examples
Input Arguments
Output Arguments
Tips
Starting in R2016b, instead of using the
step
command to update model parameter estimates, you can call the System object with input arguments, as if it were a function. For example,[A,EstimatedOutput] = step(obj,y)
and[A,EstimatedOutput] = obj(y)
perform equivalent operations.
Version History
Introduced in R2015b
See Also
release
| reset
| clone
| isLocked
| recursiveAR
| recursiveARX
| recursiveARMA
| recursiveARMAX
| recursiveBJ
| recursiveOE
| recursiveLS