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A grid‐based tool for optimal performance monitoring of a glycemic regulator
Author(s) -
Ávila Luis,
Martínez Ernesto
Publication year - 2015
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2220
Subject(s) - artificial pancreas , regulator , control theory (sociology) , computer science , grid , reliability (semiconductor) , optimal control , markov chain , markov decision process , glycemic , mathematical optimization , control engineering , markov process , mathematics , control (management) , engineering , artificial intelligence , machine learning , type 1 diabetes , insulin , endocrinology , chemistry , biochemistry , geometry , medicine , gene , power (physics) , quantum mechanics , diabetes mellitus , statistics , physics
Summary Recent technology breakthroughs towards a fully automated artificial pancreas give rise to the need of new monitoring tools aiming at increasing both reliability and performance of a closed‐loop glycemic regulator. Based on error grid analysis, an insightful monitoring tool is proposed to assess if a given closed‐loop implementation respects its specification of an optimally performing glycemic regulator under uncertainty. The optimal behavior specification is obtained using linearly solvable Markov decision processes, whereby the Bellman optimality equation is made linear through an exponential transformation that allows obtaining the optimal control policy in an explicit form. The specification for the desired glucose dynamics is learned using Gaussian processes for state transitions in an optimally performing artificial pancreas. By means of the proposed grid, the specification is vis‐à‐vis compared with glucose sensor readings so that any significant deviation from the expected closed‐loop performance under abnormal or faulty scenarios can be detected. Copyright © 2015 John Wiley & Sons, Ltd.