Estimates the B and D matrices in discrete-time LTI state-space models from input-output measurements.


[B,D] = dac2bd(A,C,u,y)

[B,D] = dac2bd(A,C,u1,y1,...,up,yp)


This function estimates the B and D matrices corresponding to a discrete-time LTI state-space model. The estimate is based on the measured input-output data sequences, and on the A and C matrices, which are possibly estimated using dmodpo, dmodpi or dmodrs. Several data batches can be concatenated.


A is the state-space model's A matrix.

C is the state-space model's C matrix.

u,y is the measured input-output data from the system to be identified.

Multiple data batches can be specified by appending additional u,y pairs to the parameter list.


B is the state-space model's B matrix.

D is the state-space model's B matrix.


Estimating B,D and the initial state x0 from input-output data and A and C is a linear regression [1]:

The regression matrix Phi and data matrix theta are given by:

The function ltiitr is used to efficiently fill the regression matrix Phi.

Used By

This a top-level function that is used directly by the user.

Uses Functions


See Also

dac2b, dmodpo, dmodpi, dmodrs, ltiitr


[1] B. Haverkamp, Subspace Method Identification, Theory and Practice. PhD thesis, Delft University of Technology, Delft, The Netherlands, 2000.