Lyapunov-based neural network model predictive control using metaheuristic optimization approach

C Stiti, M Benrabah, A Aouaichia, A Oubelaid… - Scientific Reports, 2024 - nature.com
This research introduces a new technique to control constrained nonlinear systems, named
Lyapunov-based neural network model predictive control using a metaheuristic optimization …

The evolution of control algorithms in artificial pancreas: A historical perspective

G Quiroz - Annual Reviews in Control, 2019 - Elsevier
Blood glucose control algorithms have evolved since the beginnings of the artificial
pancreas in diabetes treatment. Although the main problem to solve remains as the …

Review of the Omnipod® 5 Automated Glucose Control System Powered by Horizon™ for the Treatment of Type 1 Diabetes

EC Cobry, C Berget, LH Messer… - Therapeutic Delivery, 2020 - Taylor & Francis
Type 1 diabetes (T1D) is a medical condition that requires constant management, including
monitoring of blood glucose levels and administration of insulin. Advancements in diabetes …

First outpatient evaluation of a tubeless automated insulin delivery system with customizable glucose targets in children and adults with type 1 diabetes

GP Forlenza, BA Buckingham, SA Brown… - Diabetes technology …, 2021 - liebertpub.com
Background: The objective of this study was to assess the safety and effectiveness of the first
commercial configuration of a tubeless automated insulin delivery system, Omnipod® 5, in …

Velocity-weighting & velocity-penalty MPC of an artificial pancreas: Improved safety & performance

R Gondhalekar, E Dassau, FJ Doyle III - Automatica, 2018 - Elsevier
Abstract A novel Model Predictive Control (MPC) law for the closed-loop operation of an
Artificial Pancreas (AP) to treat type 1 diabetes is proposed. The contribution of this paper is …

Adaptive zone model predictive control of artificial pancreas based on glucose-and velocity-dependent control penalties

D Shi, E Dassau, FJ Doyle - IEEE Transactions on Biomedical …, 2018 - ieeexplore.ieee.org
Objective: Zone model predictive control (MPC) has been proven to be an efficient approach
to closed-loop insulin delivery in clinical studies. In this paper, we aim to safely reduce mean …

Advanced hybrid artificial pancreas system improves on unannounced meal response-In silico comparison to currently available system

J Garcia-Tirado, D Lv, JP Corbett, P Colmegna… - Computer Methods and …, 2021 - Elsevier
Background and objective: Glycemic control, especially meal-related disturbance rejection,
has proven to be a major challenge for people with type 1 diabetes. In this manuscript, we …

Event-triggered model predictive control for embedded artificial pancreas systems

A Chakrabarty, S Zavitsanou, FJ Doyle… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Objective: The development of artificial pancreas (AP) technology for deployment in low-
energy, embedded devices is contingent upon selecting an efficient control algorithm for …

Safety and feasibility of the OmniPod hybrid closed-loop system in adult, adolescent, and pediatric patients with type 1 diabetes using a personalized model predictive …

BA Buckingham, GP Forlenza, JE Pinsker… - Diabetes technology …, 2018 - liebertpub.com
Background: The safety and feasibility of the OmniPod personalized model predictive control
(MPC) algorithm in adult, adolescent, and pediatric patients with type 1 diabetes were …

Plasma-insulin-cognizant adaptive model predictive control for artificial pancreas systems

I Hajizadeh, M Rashid, A Cinar - Journal of process control, 2019 - Elsevier
An adaptive model predictive control (MPC) algorithm with dynamic adjustments of
constraints and objective function weights based on estimates of the plasma insulin …