Representation power of State Space Models

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We can represent subclass of linear time invariant (LTI) systems with State Space Representation:

$$\dot X = AX + BU,$$ $$Y = CX + DU.$$

Also, nonlinear systems are formulated with generalized State Space Representation where the functions could be nonlinear:

$$\dot X=f(X,U,t),$$ $$Y = g(X,U,t).$$

The question is, what is their representation power? Can we formulate any system in State Space Model?

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It depends on how much you "generalize" the state space representation when dealing with non-linear dynamical systems.

$$ \dot X = f\left( {X,U,t} \right)\quad \quad Y = g\left( {X,U,t} \right)$$

The general consensus is that in the above generalizations derivatives of the input $U$ are absent. However, one may indeed have systems of the form $ \dot x = f\left( {x,\dot u} \right) $ and some work has been done by Freedman and Willems on conditions under which they can be cast into the form $ \dot z = g\left( {z,u} \right);x = h\left( {z,u} \right)$.

It is known that given an arbitrary system satisfying the form of generalized controller canonical representation obtaining a state-space representation from it is a hard problem. More so if the representation desired is affine in $U$.