Estimates the B matrix in discrete-time LTI state-space models from input-output measurements.
B = dac2bd(A,C,u,y)
B = dac2b(A,C,u1,y1,...,up,yp)
This function estimates the B matrix 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. The D matrix is assumed to be zero. 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.
Estimating B and the initial state x0 from input-output data and A and C is a linear regression :
The regression matrix Phi and data matrix theta are given by:
The function ltiitr is used to efficiently fill the regression matrix Phi.
This a top-level function that is used directly by the user.
 B. Haverkamp, Subspace Method Identification, Theory and Practice. PhD thesis, Delft University of Technology, Delft, The Netherlands, 2000.