You have three variables: flap, elevator, and throttle. I would try to minimize drag by controlling all three variables at once, not using separate 1-dimensional minimizations. My x variable would have x(1) = flap, x(2) = elevator, and x(3) = throttle. You almost certainly have bounds on these variables. So, depending on your available toolboxes, I would either use fmincon from Optimization Toolbox, or patternsearch from Global Optimization Toolbox, because these solvers allow you to impose bounds.
If you use fmincon, I suggest that you read about optimizing a simulation or ODE, in particular, about setting larger-than-default finite differences.
You will have to figure out for yourself how to connect your Simulink model to an optimizer, I am not familiar enough with Simulink to give you a good answer.
Alan Weiss
MATLAB mathematical toolbox documentation
