Markovian framework for diabetes control

We present management of diabetes mellitus as a constrained control problem, with very sparse sampling, where no information on dynamics are available. This problem has been approached through modelling of the system as a Markov Decision Process, and through direct derivation of control rules. Considering the complexity of the system constraints imposed by lack of information, we argue that non-model based control is the best and simplest method for this problem.