The artificial pancreas aims at the automatic delivery of insulin for glycemic control in patients with type 1 diabetes, i.e., closed-loop glucose control. One of the challenges of the artificial pancreas is to avoid controller overreaction leading to hypoglycemia, especially in the late postprandial period. In this study, an original proposal based on sliding mode reference conditioning ideas is presented as a way to reduce hypoglycemia events induced by a closed-loop glucose controller. The method is inspired in the intuitive advantages of two-step constrained control algorithms. It acts on the glucose reference sent to the main controller shaping it so as to avoid violating given constraints on the insulin-on-board. Some distinctive features of the proposed strategy are that 1) it provides a safety layer which can be adjusted according to medical criteria; 2) it can be added to closed-loop controllers of any nature; 3) it is robust against sensor failures and overestimated prandial insulin doses; and 4) it can handle nonlinear models. The method is evaluated in silico with the ten adult patients available in the FDA-accepted UVA simulator.

This brief presents a reactive reference conditioning algorithm for robot collision avoidance based on geometric invariance and sliding-mode (SM) ideas. First, constraints are defined in terms of the measurements given by the robot's sensors in order to guarantee that collisions will not occur. Then, a supervisory loop ensures the fulfillment of the constraints modifying the reference trajectory as much as necessary by means of a discontinuous control law. The proposed algorithm activates only when the constraints are about to be violated and, thus, in contrast to conventional SM approaches, there exists no reaching mode to the limit surface of the constraints (sliding surface). The validity and effectiveness of the proposed approach is substantiated by simulation and experimental results using a mobile robot equipped with infrared sensors.