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Authors: Humberto A. Silva 1 ; Celina P. Leão 2 and Eurico A. Seabra 3

Affiliations: 1 Instituto Federal de Ciencia e Tecnologia do Rio Grande do Norte,Natal/RN and Brazil. ; 2 Departamento de Produção e Sistemas, Escola de Engenharia da Universidade do Minho, Guimarães and Portugal. ; 3 Departamento de Engenharia Mecânica, Escola de Engenharia da Universidade do Minho, Guimarães and Portugal.

Keyword(s): Blood Pressure Control, Predictive Control, Multi-Model, Sensitivity Analysis.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Modeling, Analysis and Control of Discrete-event Systems ; Signal Processing, Sensors, Systems Modeling and Control ; System Modeling

Abstract: Postsurgical complication of hypertension may occur in cardiac patients. To decrease the chances of complication it is necessary to lower high blood pressure as soon as possible. Continuous infusion of vasodilator drugs, such as sodium nitroprusside (Nipride), would quickly lower the blood pressure in most patients. However, each patient has a different sensitivity to infusion of Nipride. The parameters and the time delays of the blood pressure control system are initially unknown. Moreover, the parameters of the transfer function associated with a particular patient change over time. The objective of the study is to develop a procedure for blood pressure control in the presence of uncertainty of parameters and considerable time delays. In this paper, a sensitivity analysis was performed, changing the parameter that controls the convergence rate of weight factors (V). The simulation results showed significant changes in settling time (Ts), stressing the importance of this parameter o n the control model definition. Considering a V = 0.05 was obtained Ts = 195s and, for same patient, Ts = 510s by increasing the value to V = 0.4, with the Root Mean Square Error (RMSE) varying but always lower than 1%. (More)

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Paper citation in several formats:
Silva, H.; Leão, C. and Seabra, E. (2018). Parametric Sensitivity Analysis of a Multiple Model Adaptive Predictive Control for Regulation of Mean Arterial Blood Pressure. In Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-321-6; ISSN 2184-2809, SciTePress, pages 510-516. DOI: 10.5220/0006909805100516

@conference{icinco18,
author={Humberto A. Silva. and Celina P. Leão. and Eurico A. Seabra.},
title={Parametric Sensitivity Analysis of a Multiple Model Adaptive Predictive Control for Regulation of Mean Arterial Blood Pressure},
booktitle={Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2018},
pages={510-516},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006909805100516},
isbn={978-989-758-321-6},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Parametric Sensitivity Analysis of a Multiple Model Adaptive Predictive Control for Regulation of Mean Arterial Blood Pressure
SN - 978-989-758-321-6
IS - 2184-2809
AU - Silva, H.
AU - Leão, C.
AU - Seabra, E.
PY - 2018
SP - 510
EP - 516
DO - 10.5220/0006909805100516
PB - SciTePress