A centralized multi-objective model predictive control for a biventricular assist device: An in silico evaluation

Koh, Vivian Ci Ai and Ho, Yong Kuen and Stevens, Michael Charles and Ng, Boon Chiang and Salamonsen, Robert Francis and Lovell, N.H. and Lim, Einly (2019) A centralized multi-objective model predictive control for a biventricular assist device: An in silico evaluation. Biomedical Signal Processing and Control, 49. pp. 137-148. ISSN 1746-8094, DOI https://doi.org/10.1016/j.bspc.2018.10.021.

Full text not available from this repository.
Official URL: https://doi.org/10.1016/j.bspc.2018.10.021

Abstract

Speed regulation of dual left ventricular assist devices (LVADs) as a biventricular assist device (BiVAD) may be complicated by process interactions in a cardiovascular-biventricular assist device (CVS-BiVAD) environment. In this work, a conventional centralized model predictive control (MPC) algorithm that could handle process interactions in a multivariable control problem was modified to cater for the state and time-varying factors of the CVS-BiVAD system as well as to include multiple control objectives. Referred to as the centralized multi-objective model predictive control (CMO-MPC), the scheme's control objectives aim to: a) adapt pump flow rate according to the approximate Frank-Starling (FS) mechanism, b) avoid ventricular suction, and c) avoid vascular congestion. The control performance of the CMO-MPC was benchmarked with two non-centralized control schemes: the constant-speed (CS) control and the standard Frank-Starling like proportional-integral (PI-FS) control under two patient scenarios: exercise and postural change. Simulation results revealed that the CMO-MPC avoided suction and congestion in both patient scenarios as compared to the CS control and the PI-FS control, based on the assumptions made on risks of suction and congestion events. It is therefore proposed that the CMO-MPC should be a safe physiological controller for dual LVADs in the future when reliable pressure and flow sensors become clinically available.

Item Type: Article
Funders: University of Malaya Research Grant (FP008-2016), National Health and Medical Research Council Centre for Research Excellence in Advanced Cardio-respiratory Therapies Improving OrgaN Support (ACTIONS) (APP1079421)
Uncontrolled Keywords: Frank-Starling (FS) mechanism; Physiological control; Ventricular suction; Vascular congestion
Subjects: R Medicine
Divisions: Faculty of Medicine
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 17 Jan 2019 04:42
Last Modified: 17 Jan 2019 04:42
URI: http://eprints.um.edu.my/id/eprint/20045

Actions (login required)

View Item View Item