Development of a model predictive controller for an artificial pancreas

2017 ◽  
Author(s):  
M. El Hachimi ◽  
A. Ballouk ◽  
I. Khelafa ◽  
A. Baghdad
Keyword(s):  
Artificial Pancreas ◽  
Model Predictive Controller ◽  
Predictive Controller

An Automatic Insulin Infusion System Based on Kalman Filtering Model Predictive Control Technique

2020 ◽  
Vol 143 (2) ◽  
Author(s):  
Akshaya Kumar Patra ◽  
Anuja Nanda
Keyword(s):  
Kalman Filtering ◽  
Type I Diabetes ◽  
Artificial Pancreas ◽  
State Space Model ◽  
Control Technique ◽  
Type I ◽  
Model Predictive Controller ◽  
Clinical Disorders ◽  
Predictive Controller ◽  
Result Analysis

Abstract During the past few decades, optimal control of blood glucose (BG) concentration with adequate feedback loop has been of ample importance for Type-I diabetes mellitus (TIDM) patients as far as an artificial pancreas realization is concerned. Now-a-days, in addition to the BG control, the design of the micro-insulin dispenser (MID) with a robust control algorithm to regulate the other chronic clinical disorders based on prolonged medications is also quite indispensable. A novel Kalman filtering model predictive controller (KFMPC) has been proposed in this work to solve the aforementioned problem. For designing of the KFMPC, a ninth-order state-space model of the TIDM patient with MID is considered. In this control strategy, the conventional model predictive controller is re-formulated with a state estimator based on the Kalman filtering methodology to improve the control execution. The justification of enhanced control performance of KFMPC is demonstrated by comparative result analysis with other published control techniques. The simulations are carried out through matlab/simulink environment, and the results indicate comparatively better control ability of the suggested algorithm to control the BG level within the normoglycemic range (70–120 mg/dl) as far as accuracy, stability, quick damping, and robustness.

Accelerated model predictive controller for artificial pancreas

2018 ◽  
Vol 30 (3) ◽  
pp. 229
Author(s):  
Abdennaceur Baghdad ◽  
Mohamed El Hachimi ◽  
Abdelhakim Ballouk ◽  
Ilyass Khelafa
Keyword(s):  
Artificial Pancreas ◽  
Model Predictive Controller ◽  
Predictive Controller

scholarly journals A Constrained Model Predictive Controller for an Artificial Pancreas

2014 ◽  
Vol 47 (3) ◽  
pp. 10144-10149 ◽  
Author(s):  
Mirko Messori ◽  
Enrico Fornasiero ◽  
Chiara Toffanin ◽  
Claudio Cobelli ◽  
Lalo Magni
Keyword(s):  
Artificial Pancreas ◽  
Model Predictive Controller ◽  
Predictive Controller ◽  
Constrained Model

scholarly journals Artificial pancreas techniques based on robust model predictive controller

2019 ◽  
Vol 8 (3) ◽  
pp. 189
Author(s):  
Waleed Khalid Al-Azzawi
Keyword(s):  
Blood Glucose ◽  
Model Uncertainty ◽  
Insulin Infusion ◽  
Artificial Pancreas ◽  
Normal Range ◽  
Model Predictive Controller ◽  
Robust Model ◽  
The World ◽  
Predictive Controller ◽  
Simulation Results

Diabetes is known as the major cause of death in the world leading to kidney, retinopathy and cardiovascular diseases as well. In this paper, a Robust Model Predictive Controller (RMPC) is introduced to design artificial pancreas that solved the model uncertainty and keep the blood glucose level in the normal range by regulating the size of insulin infusion from pump based on RMPC. The simulation results will present a good performance of the proposed controller to avoid disturbance and robustness against uncertainties.

Accelerated model predictive controller for artificial pancreas

2018 ◽  
Vol 30 (3) ◽  
pp. 229
Author(s):  
Mohamed El Hachimi ◽  
Abdelhakim Ballouk ◽  
Ilyass Khelafa ◽  
Abdennaceur Baghdad
Keyword(s):  
Artificial Pancreas ◽  
Model Predictive Controller ◽  
Predictive Controller

scholarly journals Fuzzy Model Predictive Controller for Artificial Pancreas

2018 ◽  
Vol 9 (3) ◽  
pp. 1178
Author(s):  
Mohamed El Hachimi ◽  
Abdelhakim Ballouk ◽  
AbdNaceur Baghdad
Keyword(s):  
Fuzzy Logic ◽  
Artificial Pancreas ◽  
Fuzzy Model ◽  
Model Predictive Controller ◽  
Prediction Horizon ◽  
Predictive Controller ◽  
Fuzzy Logic Method ◽  
Model Predictive Controllers ◽  
Predictive Controllers ◽  
Commercial Platform

This work consists on new tuning of Model Predictive Controllers using Fuzzy Logic method. Tree relevant parameters are automatically adjusted the prediction horizon Np, the input weight R and the output weight Q. The proposed controller is implemented in an Artificial Pancreas and tested under realistic conditions in a commercial platform of simulation. The result of the simulations revealed the success of such a method to improve the controller’s performances compared to the previous ones.

Enlarging the region of stability in robust model predictive controller based on dual-mode control

2021 ◽  
pp. 014233122110123
Author(s):  
Fatemeh Khani ◽  
Mohammad Haeri
Keyword(s):  
Stability Region ◽  
Linear Matrix ◽  
Input State ◽  
Dual Mode ◽  
Model Predictive Controller ◽  
Mode Control ◽  
Robust Model ◽  
Output Constraints ◽  
Predictive Controller ◽  
The Stability

Industrial processes are inherently nonlinear with input, state, and output constraints. A proper control system should handle these challenging control problems over a large operating region. The robust model predictive controller (RMPC) could be an linear matrix inequality (LMI)-based method that estimates stability region of the closed-loop system as an ellipsoid. This presentation, however, restricts confident application of the controller on systems with large operating regions. In this paper, a dual-mode control strategy is employed to enlarge the stability region in first place and then, trajectory reversing method (TRM) is employed to approximate the stability region more accurately. Finally, the effectiveness of the proposed scheme is illustrated on a continuous stirred tank reactor (CSTR) process.

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