In this work, a low-order model designed for glucose regulation in T1DM is obtained from the UVA/Padova metabolic simulator. It captures not only the nonlinear behavior of the glucose-insulin system, but also intra-patient variations related to daily insulin sensitivity (${S_{I}}$) changes. To overcome the large inter-subject variability, the model can also be personalized based on a priori patient information. The structure is amenable for linear parameter varying (LPV) controller design, and represents the dynamics from the subcutaneous insulin input to the subcutaneous glucose output. The efficacy of this model is evaluated in comparison with a previous control-oriented model which in turn is an improvement of previous models. Both models are compared in terms of their open- and closed-loop differences with respect to the UVA/Padova model. The open-loop analysis is computed through the root mean square error (RMSE) between the glucose deviation predicted by the models and the UVA/Padova simulator. In closed-loop, the ν-gap metric is used to measure the distance in terms of closed-loop performance between the two models. The results are promising and some illustrative simulations are presented.