What are the allowable transformations on the $B$ and $C$ matrices in a linear state-space system that preserve input-to-output behavior without changing the $A$ and $D$ matrices?
I'm working with the usual state-space representation of linear system:
$$\begin{eqnarray} \frac{d}{dt}x &=& Ax + Bu \cr y &=& Cx + Du \end{eqnarray}$$
where I want to use a modal representation, namely matrix A has only real elements, and is block-diagonal with 1x1 blocks and 2x2 blocks of the form $\begin{bmatrix}a&b\cr-b&a\end{bmatrix}$ to represent complex eigenvalues. This is so that the matrix $A$ is well-conditioned.
In my case $u$ and $y$ are scalars, so $A$ is $n \times n$, $B$ is $n \times 1$, $C$ is $1 \times n$, and $D$ is $1 \times 1$. Also in my case, all the eigenvalues are unique so I don't have to worry about it being a defective matrix.
The only problem is that the writeups of modal representations always use a pure diagonal matrix, which will have complex entries for matrices with complex eigenvalues. I can figure out how to use a similarity transform with unitary matrix $T$ such that
$$\begin{eqnarray} A'&=&T^{-1}AT \cr B'&=&T^{-1}B \cr C'&=&CT \cr D'&=&D \end{eqnarray}$$
and with a suitable choice of T, I can get an $A$ matrix the way I want.
My problem is with the B and C matrices; $T$ has complex entries and seems to produce complex values for B and C. I know there are some degrees of freedom in choosing B and C (for example, I can multiply all entries of B by some constant K and divide all entries of C by K, and I get the same externally controllable + observable behavior from $u$ to $y$), but I can't figure out what I'm allowed to do to B and C if A is fixed.
I should be able to figure out how to solve the problem if I can understand the 2x2 case.
For example
$$\begin{eqnarray} \frac{d}{dt}\begin{bmatrix}x_1 \cr x_2\end{bmatrix} &=& \begin{bmatrix}-\sigma & \omega \cr -\omega & -\sigma\end{bmatrix}\begin{bmatrix}x_1 \cr x_2\end{bmatrix} + \begin{bmatrix}b_1 \cr b_2 \end{bmatrix}u \cr y &=& \begin{bmatrix}c_1 & c_2 \end{bmatrix}\begin{bmatrix}x_1 \cr x_2\end{bmatrix} + Du \end{eqnarray}$$
where $A$ has eigenvalues $-\sigma \pm j\omega$; for $D=0$ this can be used to represent the dynamic system $\frac{d^2y}{dt^2} + 2\sigma\frac{dy}{dt} + \sigma^2 + \omega^2 = k_1\frac{du}{dt} + k_2u$. There's only two degrees of freedom $(k_1,k_2)$ in the observable/controllable system, but four degrees of freedom in choosing the B and C matrices.
The transfer function is $C(sI-A)^{-1}B+D$, so something that maintains the value of $C(sI-A)^{-1}B$ will be ok. In this case as long as $C\begin{bmatrix}s+\sigma & \omega \cr -\omega & s+\sigma\end{bmatrix}B$ is preserved, the system behavior is the same.