# findAC

discrete-time system subspace identification

## Calling Sequence

    [A,C] = findAC(S,N,L,R,METH,TOL,PRINTW)
                [A,C,RCND] = findAC(S,N,L,R,METH,TOL,PRINTW)

## Arguments

S

  integer, the number of block rows in the block-Hankel matrices

N

  integer

L

  integer

R

  matrix, relevant part of the R factor of the concatenated block-Hankel matrices computed by a call to findr.

METH

  integer, an option for the method to use

  = 1

    MOESP method with past inputs and outputs;

  = 2

    N4SID method;

  Default: METH = 3.

TOL

  the tolerance used for estimating the rank of matrices. If TOL > 0, then the given value of TOL is used as a lower bound for the reciprocal condition number. Default: prod(size(matrix))*epsilon_machine where epsilon_machine is the relative machine precision.

PRINTW

  integer, switch for printing the warning messages.

  PRINTW

    = 1: print warning messages;

  = 0

    do not print warning messages.

  Default: PRINTW = 0.

A

  matrix, state system matrix

C

  matrix, output system matrix

RCND

  vector of length 4, condition numbers of the matrices involved in rank decision

## Description

finds the system matrices A and C of a discrete-time system, given the system order and the relevant part of the R factor of the concatenated block-Hankel matrices, using subspace identification techniques (MOESP or N4SID).

- [A,C] = findAC(S,N,L,R,METH,TOL,PRINTW) computes the system matrices A and C. The model structure is: x(k+1) = Ax(k) + Bu(k) + Ke(k), k >= 1, y(k) = Cx(k) + Du(k) + e(k), where x(k) and y(k) are vectors of length N and L, respectively.

- [A,C,RCND] = findAC(S,N,L,R,METH,TOL,PRINTW) also returns the vector RCND of length 4 containing the condition numbers of the matrices involved in rank decisions.

Matrix R, computed by findR, should be determined with suitable arguments METH and JOBD.

## Examples

    //generate data from a given linear system
    A = [ 0.5, 0.1,-0.1, 0.2;
          0.1, 0,  -0.1,-0.1;
         -0.4,-0.6,-0.7,-0.1;
          0.8, 0,  -0.6,-0.6];
    B = [0.8;0.1;1;-1];
    C = [1 2 -1 0];
    SYS=syslin(0.1,A,B,C);
    nsmp=100;
    U=prbs_a(nsmp,nsmp/5);
    Y=(flts(U,SYS)+0.3*rand(1,nsmp,'normal'));

    // Compute R
    S=15;L=1;
    [R,N,SVAL] = findR(S,Y',U');

    N=3;
    METH=3;TOL=-1;
    [A,C] = findAC(S,N,L,R,METH,TOL);

## See Also

- findABCD
- findBD
- findBDK
- findR
- sorder
- sident