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Neural inverse optimal control applied to type 1 diabetes mellitus patients

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Abstract

Inverse optimal trajectory tracking via a control Lyapunov function (CLF) for discrete time non-linear systems is developed and applied to type 1 diabetes mellitus patients control. The control law calculates the insulin delivery rate in order to prevent hyperglycemia and hypoglycemia levels. To synthesize the inverse optimal control law a quadratic candidate CLF is used. The proposed algorithm is tuned to follow a desired trajectory; this trajectory reproduces the glucose absorption of a healthy person. Simulation results applied for two different patients illustrate the applicability of the control law and a comparison with inverse optimal neural control via passivity is included.

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Acknowledgements

The authors thank the support CONACYT Mexico, through Projects 103191Y and 131678Y. They also thank the very useful comments of the anonymous reviewers, which help to improve the paper.

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Authors and Affiliations

  1. CINVESTAV-IPN, Unidad Guadalajara, Apartado Postal 31-438, Plaza La Luna, C.P. 45091, Guadalajara, Jalisco, Mexico

    Blanca S. Leon & Edgar N. Sanchez

  2. CUCEI, Universidad de Guadalajara, Apartado Postal 51-71, Col. Las Aguilas, C.P. 45080, Zapopan, Jalisco, Mexico

    Alma Y. Alanis & Eduardo Ruiz-Velazquez

  3. Division de Estudios de Posgrado, Facultad de Ingenieria Electrica, UMSNH, F.J. Mugica SN, Ciudad Universitaria, 58030, Morelia, Michoacán, Mexico

    Fernando Ornelas-Tellez

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  1. Blanca S. Leon
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  2. Alma Y. Alanis
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  3. Edgar N. Sanchez
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  4. Fernando Ornelas-Tellez
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Correspondence to Alma Y. Alanis.

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Leon, B.S., Alanis, A.Y., Sanchez, E.N. et al. Neural inverse optimal control applied to type 1 diabetes mellitus patients. Analog Integr Circ Sig Process 76, 343–352 (2013). https://doi.org/10.1007/s10470-013-0109-8

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  • DOI: https://doi.org/10.1007/s10470-013-0109-8

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