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Type 1 diabetes is characterized by the destruction of the only insulin producing cells in the body. The typical course of action consists of daily insulin injections or an insulin pump. Assuming available methods for online monitoring of glucose concentrations, feedback control can be applied to this problem to improve regulation of glucose concentrations. A control algorithm is presented for feedback control of glucose levels in Type 1 patients. The control problem may be viewed as asymmetric, with negative variation from normal values treated with a more aggressive response than positive deviation. A simple asymmetric proportional-integral (PI) controller is presented where controller parameters vary depending on the sign of the current error value. Optimal closed-loop tuning parameters for the asymmetric control system are determined using local search methods. The asymmetric control system is then considered for robustness analysis using standard techniques from linear systems theory.

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Particulate modeling is often used to describe the kinematics of granular flow in mixers, granulators, and fluidized beds. An improved understanding of the rate processes associated with granulation can prove to be a valuable tool for modeling the evolution of particle size distributions. The kinetic theory of granular flow (KTGF) is a tool developed from the kinetic theory of gases to describe the kinematics found in granular media. Past work has shown that the KTGF can be used to describe the particle motion in a fluidized bed due to the inherently random particle movement caused by the fluid mechanics. Initially, it was thought that kinetic theory would not suffice when describing the kinematics in a high-shear mixer because of the shear motion in the mixer. However, recent work by Nilpawar et al. (in Proceedings:  The 8th International Symposium on Agglomeration; The Industrial Pharmacists Group:  Bangkok, Thailand, 2005) has shown experimentally that the collision frequency caused by random motion dominates over shear-induced collisions using measurements from the surface of the mixer. The present work attempts to support previous experimental findings by investigating the distributions of particle speed and velocity. The analysis is performed using discrete element modeling (DEM), a tool commonly used to simulate complex granular flow. This work demonstrates that, under idealized conditions, the KTGF is a very adequate means of describing particle flow. As the DEM process model becomes less ideal, the KTGF appears to be less successful in modeling the system.