What's the adventages and disadventages of reducing states in state space model? - Model reduction

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In control theory, there is something called "Model reduction". That's means states from a state space model decreasing.

I know that's a small state space model, is much easier to model, that a large state space model.

For exampel. If I want to build a LQGI (Linear Quadratic Gaussian Integral) controller with analog electrical compontens such as several operation amplifiers, resistors and capacitors. It will requires a lot of those if the state space model is large.

So my question is: Can I still have an optimal controller, even if I reducing a lot of states? Or do I lose some optimal properties just by "removing" som states?

I would like to build a LQGI controller with only analog electrical components because that controller will then work in real-time, like a digital controller would not do, due to the sampling time.