A control-based observer approach for estimating energy intake during pregnancy.

Ranghetti, L; Rivera, D E; Guo, P; Visioli, A; Savage, J S; Symons Downs, D

Ranghetti, L; Rivera, D E; Guo, P; Visioli, A; Savage, J S; Symons Downs, D.

Afiliación

Ranghetti L; Department of Mechanical and Industrial Engineering, University of Brescia, Brescia, Italy.
Rivera DE; Control Systems Engineering Laboratory, School for the Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ, USA.
Guo P; Control Systems Engineering Laboratory, School for the Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ, USA.
Visioli A; Department of Mechanical and Industrial Engineering, University of Brescia, Brescia, Italy.
Savage JS; Department of Nutritional Sciences, Pennsylvania State University, University Park, PA, USA.
Symons Downs D; Exercise Psychology Laboratory, Department of Kinesiology, Pennsylvania State University, University Park, PA, USA.

Int J Robust Nonlinear Control ; 33(9): 5105-5127, 2023 Jun.

Article en En | MEDLINE | ID: mdl-37193543

Palabras clave

Energy intake estimation; Internal Model Control; Model Predictive Control; gestational weight gain; robustness

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Int J Robust Nonlinear Control Año: 2023 Tipo del documento: Article País de afiliación: Italia

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