The quest for artificial pancreas can be structured in three tasks: glucose sensor, insulin pump and control algorithm. The latter is a key point of the diabetes closing the loop problem and its primary prerequisite is a valid model able to describe the blood glucose system. Among the many models appeared in the literature, the model of Magni et al  is widely used and represents a relatively complex nonlinear model with glucose absorption as well as subcutaneous glucose and insulin dynamics incorporated into its structure. Our aim is to hide the nonlinearity of this model by transforming the signal coming from a linear controller so that the response of the model would mimic the behavior of a linear system, desirably the one acquired through steady-state linearization; hence the validity of linear controllers could be extended. The nonlinear method known as asymptotic tracking of a linear system and presented in , needs the values of the state variables; hence a Kalman-filter extended for nonlinear systems is used. The capabilities of this approach are examined through simple control algorithms and realistic input scenarios.