A deep analysis on optimization techniques for appropriate PID tuning to incline efficient artificial pancreas

Abstract

Juvenile diabetes or a type-1 diabetic can be seen in 5% of the patients, who affected by this form of the disease. The type-1 diabetic can be seen mostly in children and young adults, which continue to spread all over the world. The developments of the artificial pancreas give hope to develop glucose monitoring sensors and insulin pump for those who suffer from severe lack of insulin generation. On the other hand, taking control of blood sugar is a challenging task in which specific factors of the body will limit the ability of closed-loop systems to perform well. This paper presents an investigation of the optimized control strategy to deal with the closed-loop artificial pancreas, which is based on the proportional–integral–derivative (PID). The primary objective of this investigation is to find the best optimized model to maintain the best glucose monitoring and insulin delivery. In order to tune the PID controller to decide on the efficient insulin injection, an investigation was conducted for an optimization algorithm [such as genetic algorithm, gravitational search algorithm, particle swarm optimization, sequential randomized algorithm, brain storm optimization algorithm, class topper optimization, and gray wolf optimization algorithm (GWOA)]. Among these, it is found that the GWOA gives a promising result compare to the other.

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Correspondence to Nagaraj Balakrishnan.

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Balakrishnan, N., Nisi, K. A deep analysis on optimization techniques for appropriate PID tuning to incline efficient artificial pancreas. Neural Comput & Applic 32, 7587–7596 (2020). https://doi.org/10.1007/s00521-018-3687-7

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Keywords

  • GA
  • GSA
  • PSO
  • SRA
  • BSOA
  • CTOA
  • GWOA
  • Optimization
  • PID controllers