robustify is used to derive a robust counterpart of an uncertain optimization problem (constraints satisfied for all possible uncertainties, and worst-case objective).
Consider the following uncertain problem (w is the uncertain variable)
F = [x+w <= 1];
W = [uncertain(w),-0.5 <= w <= 0.5];
objective = -x;
The problem can be solved immediately
Alternatively, we can first derive a robust version.
This model does not involve the uncertain variable anymore, and corresponds to the worst-case scenario model. We can now solve the model.