Receding Horizon Control of Type 1 Diabetes Mellitus by Using Nonlinear Programming

Hamza Khan, József K. Tar, Imre Rudas, Levente Kovács and György Eigner

Complexity, 2018, vol. 2018, 1-11

Abstract:

Receding Horizon Controllers are one of the mostly used advanced control solutions in the industry. By utilizing their possibilities we are able to predict the possible future behavior of our system; moreover, we are able to intervene in its operation as well. In this paper we have investigated the possibilities of the design of a Receding Horizon Controller by using Nonlinear Programming. We have applied the developed solution in order to control Type 1 Diabetes Mellitus. The nonlinear optimization task was solved by the Generalized Reduced Gradient method. In order to investigate the performance of our solution two scenarios were examined. In the first scenario, we applied “soft” disturbance—namely, smaller amount of external carbohydrate—in order to be sure that the proposed method operates well and the solution that appeared through optimization is acceptable. In the second scenario, we have used “unfavorable” disturbance signal—a highly oscillating external excitation with cyclic peaks. We have found that the performance of the realized controller was satisfactory and it was able to keep the blood glucose level in the desired healthy range—by considering the restrictions for the usable control action.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:4670159

DOI: 10.1155/2018/4670159

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