Ant colony optimization for model predictive control for blood glucose regulation

Please use this identifier to cite or link to this item: https://doi.org/10.1145/2350716.2350749

Title:	Ant colony optimization for model predictive control for blood glucose regulation
Authors:	Ho, Y. Nguyen, B.P. Chui, C.-K.
Keywords:	Ant colony optimization Artificial pancreas Model predictive control
Issue Date:	2012
Citation:	Ho, Y.,Nguyen, B.P.,Chui, C.-K. (2012). Ant colony optimization for model predictive control for blood glucose regulation. ACM International Conference Proceeding Series : 214-217. ScholarBank@NUS Repository. https://doi.org/10.1145/2350716.2350749
Abstract:	This paper presents an adaptation of the Ant System method to find the optimal control input for blood glucose regulation using Model Predictive Control (MPC). The Ant System optimization method was implemented to solve a linear MPC problem and performance was compared with the interior point method for optimization. The Ant System was found to perform well for the linear MPC problem and has the advantage over the interior point method as it can extended for use with non-linear MPC problems. Copyright © 2012 ACM.
Source Title:	ACM International Conference Proceeding Series
URI:	http://scholarbank.nus.edu.sg/handle/10635/51562
ISBN:	9781450312325
DOI:	10.1145/2350716.2350749
Appears in Collections:	Staff Publications

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