Full Closed-Loop Tests for the Relay Feedback Autotuning of Stable, Integrating, and Unstable Processes.

The relay (on-off) controller can stabilize wide ranges of processes including open-loop stable, integrating, and unstable processes, producing sustained oscillations. For improved proportional-integral-derivative controller tunings, methods to find process models with mixed closed-loop tests of relay feedback and proportional-derivative (PD) controllers are proposed. For unknown processes with arbitrary initial states, relay feedback tests are first applied and, after cyclic steady states are obtained, PD controllers or other relay feedback tests with set point changes are followed.

Modeling of tumor growth undergoing virotherapy.

Tumor growth models subject to virotherapy treatment are analyzed and compared in this paper. Tumor growth conditions are obtained for each model type based on the virus infection rate and immune suppressive drug delivery. Equilibrium conditions resulted into quadratic functions for which the tumor radius remained constant during virotherapy.

Effectiveness of Intravenous Infusion Algorithms for Glucose Control in Diabetic Patients Using Different Simulation Models.

The effectiveness of closed-loop insulin infusion algorithms is assessed for three different mathematical models describing insulin and glucose dynamics within a Type I diabetes patient. Simulations are performed to assess the effectiveness of proportional plus integral plus derivative (PID) control, feedforward control, and a physiologically-based control system with respect to maintaining normal glucose levels during a meal and during exercise. Control effectiveness is assessed by comparing the simulated response to a simulation of a healthy patient during both a meal and exercise and establishing maximum and minimum glucose levels and insulin infusion levels, as well as maximum duration of hyperglycemia.

In Vivo Simulations of the Intravenous Dynamics of Submicron Particles of pH-Responsive Cationic Hydrogels in Diabetic Patients.

A mathematical model describing glucose-dependent pH swelling and insulin release is developed for pH-sensitive cationic hydrogels in which glucose oxidase and catalase have been immobilized and insulin imbibed. Glucose based swelling and insulin release are simulated for intravenously injected particles at various design conditions. The effects of particle size, the number of injected particles, insulin loading, enzyme loading, monomer functional group loading and pK(a), and hydrogel crosslinking ratio on insulin release and glucose sensitivity are investigated in order to optimally design the device for use.

Parameter set uniqueness and confidence limits in model identification of insulin transport models from simulation data.

Background: The use of patient models describing the dynamics of glucose, insulin, and possibly other metabolic species associated with glucose regulation allows diabetes researchers to gain insights regarding novel therapies via simulation. However, such models are only useful when model parameters are effectively estimated with patient data.

Methods: The use of least squares to effectively estimate model parameters from simulation data was investigated by observing factors that influence the accuracy of estimates for the model parameters from a data set generated using a model with known parameters.

The future of open- and closed-loop insulin delivery systems.

We have analysed several aspects of insulin-dependent diabetes mellitus, including the glucose metabolic system, diabetes complications, and previous and ongoing research aimed at controlling glucose in diabetic patients. An expert review of various models and control algorithms developed for the glucose homeostasis system is presented, along with an analysis of research towards the development of a polymeric insulin infusion system. Recommendations for future directions in creating a true closed-loop glucose control system are presented, including the development of multivariable models and control systems to more accurately describe and control the multi-metabolite, multi-hormonal system, as well as in-vivo assessments of implicit closed-loop control systems.