Undesired model reduction

Hello,
It seems to me that when I try to define a non-minimal state representation (e.g. with a state that can't be controlled or that doesn't have a dynamic) the system returned by the StateSpace class is automatically reduced, by eliminating such "non meaningful" states.
As example consider the following code:

from control import StateSpace

a = [[0., 0., 0.], [0., 0., 0.], [0., 0., 0.]]
b = [[1, 0], [0, 0], [0, 1]]
c = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]
d = [[0, 0], [0, 0], [0, 0]]
x = StateSpace(a,b,c,d)

the obtained state representation is the following :

>>> x
A = [[0. 0.]
 [0. 0.]]

B = [[1. 0.]
 [0. 1.]]

C = [[1. 0.]
 [0. 0.]
 [0. 1.]]

D = [[0. 0.]
 [0. 0.]
 [0. 0.]]

where the second state has been removed. Is it possible to not have this automatic model reduction (regardless of the fact that such state is not meaningful ) ? I couldn't find anything in the documentation