Drake: any tutorial or example for nonlinear model predictive control?

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I am currently learning the usage of the MIT Drake library for optimization and would like to formulate a nonlinear model predictive control problem. I notice that the pydrake examples show the methods to add nonlinear costs and constraints in a nonlinear program problem. However, I am not sure how to integrate nonlinear (and maybe even switching) system dynamics into the optimization problem. Are there any related examples or useful hints? Any help would be much appreciated.

Thanks,

Keran

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