idssdata
Statespace data of identified system
Syntax
[A,B,C,D,K]
= idssdata(sys)
[A,B,C,D,K,x0] = idssdata(sys)
[A,B,C,D,K,x0,dA,dB,dC,dD,dK,dx0] = idssdata(sys)
[A,B,C,D,K,___]
= idssdata(sys,j1,...,jN)
[A,B,C,D,K,___]
= idssdata(sys,'cell')
Description
[A,B,C,D,K]
= idssdata(sys) returns the A,B,C,D
and K matrices of the identified statespace model sys.
[A,B,C,D,K,x0] = idssdata(sys) returns
the initial state values, x0.
[A,B,C,D,K,x0,dA,dB,dC,dD,dK,dx0] = idssdata(sys) returns
the uncertainties in the system matrices for sys.
[A,B,C,D,K,___]
= idssdata(sys,j1,...,jN) returns
data for the j1, ..., jn entries in the model array sys.
[A,B,C,D,K,___]
= idssdata(sys,'cell') returns
data for all the entries in the model array sys as
separate cells in cell arrays.
sys 
Identified model.
If sys is not an identified statespace
model (idss or idgrey),
then it is first converted to an idss model.
This conversion results in a loss of the model uncertainty information.
sys may be an array of identified models.

j1,...,jN 
Integer indices of N entries in the array sys of
identified systems.

Output Arguments
A,B,C,D,K 
Statespace matrices that represent sys as:
If sys is an array of identified models,
then A,B,C,D,K are multidimension arrays. To
access the statespace matrix, say A, for the kth
entry of sys, use A(:,:,k).

x0 
Initial state.
If sys is an idss or idgrey model,
then x0 is the value obtained during estimation.
It is also stored using the Report.Parameters property
of sys.
For other model types, x0 is zero.
If sys is an array of identified models,
then x0 contains a column for each entry in sys.

dA,dB,dC,dD,dK 
Uncertainties associated with the statespace matrices A,B,C,D,K.
The uncertainty matrices represents 1 standard deviation of
uncertainty.
If sys is an array of identified models,
then dA,dB,dC,dD,dK are multidimension arrays.
To access the statespace matrix, say A, for the kth
entry of sys, use A(:,:,k).

dx0 
Uncertainty associated with the initial state.
dx0 represents 1 standard deviation of
uncertainty.
If sys is an array of identified models,
then dx0 contains a column for each entry in sys.

Examples
expand all
Obtain the identified statespace matrices
for a model estimated from data.
Identify a model using data.
load icEngine.mat
data = iddata(y,u,0.04);
sys = n4sid(data,4,'InputDelay',2);
data is an iddata object
representing data sampled at a sampling rate of 0.04 seconds.
sys is an idss model representing
the identified system.
Obtain identified statespace matrices of sys.
[A,B,C,D,K] = idssdata(sys);
A,B,C,D and K represent
the statespace matrices of the identified model sys.
Obtain the initial state associated with an
identified model.
Identify a model using data.
load icEngine.mat
data = iddata(y,u,0.04);
sys = n4sid(data,4,'InputDelay',2);
data is an iddata object
representing data sampled at a sampling rate of 0.04 seconds.
sys is an idss model representing
the identified system.
Obtain the initial state associated with sys.
[A,B,C,D,K,x0] = idssdata(sys);
A,B,C,D and K represent
the statespace matrices of the identified model sys.
x0 is the initial state identified for sys.
Obtain the uncertainty matrices of the statespace
matrices of an identified model.
Identify a model using data.
load icEngine.mat
data = iddata(y,u,0.04);
sys = n4sid(data,4,'InputDelay',2);
data is an iddata object
representing data sampled at a sampling rate of 0.04 seconds.
sys is an idss model representing
the identified system.
Obtain the uncertainty matrices associated with the statespace
matrices of sys.
[A,B,C,D,K,x0,dA,dB,dC,dD,dx0] = idssdata(sys);
dA,dB,dC,dD and dK represent
the uncertainty associated with the statespace matrices of the identified
model sys.
dx0 represents the uncertainty associated
with the estimated initial state.
Obtain the statespace matrices for multiple
models from an array of identified models.
Identify multiple models using data.
load icEngine.mat
data = iddata(y,u,0.04);
sys2 = n4sid(data,2,'InputDelay',2);
sys3 = n4sid(data,3,'InputDelay',2);
sys4 = n4sid(data,4,'InputDelay',2);
sys = stack(1,sys2,sys3,sys4);
data is an iddata object
representing data sampled at a sampling rate of 0.04 seconds.
sys is an array of idss models.
The first entry of sys is a second order identified
system. The second and third entries of sys are
third and fourth order identified systems, respectively.
Obtain the statespace matrices for the first and third
entries of sys.
[A,B,C,D,K,x0] = idssdata(sys,1,3);
Obtain the statespace matrices of an array
of identified models in cell arrays.
Identify multiple models using data.
load icEngine.mat
data = iddata(y,u,0.04);
sys3 = n4sid(data,3,'InputDelay',2);
sys4 = n4sid(data,4,'InputDelay',2);
sys = stack(1,sys3,sys4);
data is an iddata object
representing data sampled at a sampling rate of 0.04 seconds.
sys is an array of idss models.
The first entry of sys is a third order identified
system and the second entry is a fourth order identified system.
Obtain the statespace matrices of sys in
cell arrays.
[A,B,C,D,K,x0] = idssdata(sys,'cell');
A,B,C,D and K are
cell arrays containing the statespace matrices of the individual
entries of the identified model arraysys.
x0 is a cell array containing the estimated
initial state of the individual entries of the identified model array sys.
See Also
idss  polydata  ssdata  tfdata  zpkdata