If the identified model has complex poles, you can't wish them away by converting to zpk. Note that complex poles come in conjugate pairs, so a real filter can still be created. If you are looking for a modal separation (sum of first and second order transfer functions), see modalfit in Signal Processing Toolbox.
Regarding high order TF identification with TFEST: Note that a high order transfer function is going to be ill-conditioned. If you need to work with such high orders, I would stringly suggest using state-space identification (see SSEST).