State space system identification Suppose I have a real (physical) dynamical system with some sensors and actuators, and I also have an idealized state-space model of this same system.  How, in general, can I adjust the model to match the real system?

My experience is with frequency-domain analysis.  My first reaction would be to measure swept-sine transfer functions, and to calculate parameters of my system from the location of resonances or poles in the measured data.  

Is there a better, more general technique for system identification in the state-space representation?
The experimental frequency domain data gives you information on the input-output behavior of the system. If the system is assumed to be linear and time-invariant (LTI), this information will be in the form of a transfer function. Given a transfer function, there are infinitely many state-space realizations that yield the same input-output behavior and, thus, are I/O-equivalent.

Having said that, you may want to take a look at the Adaptive Control literature.