Intelligent Observer-Based Controller Design for Nonlinear Type-1 Diabetes Model via Adaptive Neural Network Method
Open Access
- 7 July 2021
- journal article
- Published by ASCEE Publications in International Journal of Robotics and Control Systems
- Vol. 1 (3), 338-354
- https://doi.org/10.31763/ijrcs.v1i3.442
Abstract
Diabetes is an increasing health problem all around the world, particularly Type 1 diabetes (T1D), people with T1D require precise glycemic control, due to a shortage of insulin production. This paper introduces a new adaptive neural observer-based controller for a class of nonlinear T1D systems. A solution is proposed to guarantees practical tracking of a desired glucose concentration by a new adaptive neural observer-based control strategy. One of the intelligence procedures is the network under online learning that the mentioned controller is learned by a back-propagation algorithm. This network is a significant class of feed-forward artificial neural networks that maps a set of inputs into a set of proper outputs. Guarantee stability of observer and controller by Lyapunov direct and training online are the merit of the method. Also, despite the presence of internal and external uncertainties, the multilayer perceptron neural observer-based controller is robust. The performance of the proposed method is hopeful based on the results.Keywords
This publication has 28 references indexed in Scilit:
- Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4·4 million participantsThe Lancet, 2016
- Neural estimation using a stable discrete-time MLP observer for a class of discrete-time uncertain MIMO nonlinear systemsNonlinear Dynamics, 2016
- Intelligent nonlinear observer design for a class of nonlinear discrete-time flexible joint robotIntelligent Service Robotics, 2014
- Designing Controller for Joined Dynamic Nonlinear PEMFC and Buck Converter SystemInternational Journal of Power Electronics and Drive Systems (IJPEDS), 2014
- Design Controller for a Class of Nonlinear Pendulum Dynamical SystemIAES International Journal of Artificial Intelligence (IJ-AI), 2013
- The epidemic of type 1 diabetesCurrent Opinion in Endocrinology, Diabetes and Obesity, 2011
- Mathematical modelling of immune regulation of type 1 diabetesBiosystems, 2010
- Predicting blood glucose levels in diabetics using feature extraction and Artificial Neural NetworksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2008
- Recent progress in analytical instrumentation for glycemic control in diabetic and critically ill patientsAnalytical and Bioanalytical Chemistry, 2007
- A Model of β -Cell Mass, Insulin, and Glucose Kinetics: Pathways to DiabetesJournal of Theoretical Biology, 2000