For nonlinear mpc, the easiest way to do that is to use the multistage formulation and block. Then you can set constraints/cost for the final stage to accomplish what you need. Here is an example that you can use as a reference.
You could also do the same with the generic nonlinear MPC formulation that you are currently using, but it is a bit more complex. An example that you can follow is here. Here, you would need to provide constraints and weights as vectors for the entire prediction horizon, for each time step. So you can see how much more convenient the multistage formulation is where you have the flexibility to define cost/constraints at every stage/time step.
