The problem of designing the identification experiments to make them maximally informative with respect to the intended model use is studied. The focus is on how to identify models that are good for control, so called "Identification for Control". A main result is that we derive explicit expressions for the optimal controller and the optimal reference signal spectrum to use in the identification experiment for the case that only the misfit in the dynamics model is penalized and when a linear combination of the input and output variances is constrained.