Is it possible to use Simulink model as prediction model in MPC?

Hi.

I have read the documentation on MPC Design including liniear, non-linear and other controllers and checked all examples and all of them use some special analythical "prediction model" for MPC Controller block.

But my question is: since there is usually a Simulink plant model created to validate controller response, why this model could not be used as prediction model in MPC controller? This means that MPC controller simply should run few Simulink simulations every time step to calculate expected plant response with different inputs and then select the optimized values.

I know this will consume a lot of CPU resources, but would simplify MPC design a lot, as no separate "data-driven" or linearized models are required.

One typical example would be a house heater controller. Example https://www.mathworks.com/help/mpc/ug/use-multistage-mpc-with-neural-state-space-prediction-model-for-house-heating.html uses system identification toolbox and neural state space model to design prediction model. But why one should do so if the house plant Simscape model already exists in simulation and can be used directly by MPC Controller for prediction?

Am I'm missing something?

[Mr. Pavl M.]

   Let's construct in reality under real world constraints, can you obtain the internal plant distinct states vector accurate spatio-temporal datum? I think they made so because the internal states value-temporal waveforms are closed and can't be extracted during controller run, can the prediction model be constructed with just state and disturbance estimators?