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

•The proposed model predictive control is a centralized multi-objective control.•Centralized control scheme is ideal control problems with process interactions.•Multi-objective control explicitly avoids suction and congestion.•Predictive scheme pre-empts suction and congestion by early control updat...

Full description

Saved in:
Bibliographic Details
Published inBiomedical signal processing and control Vol. 49; pp. 137 - 148
Main Authors Koh, V.C.A., Ho, Y.K., Stevens, M.C., Ng, B.C., Salamonsen, R.F., Lovell, N.H., Lim, E.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.03.2019
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:•The proposed model predictive control is a centralized multi-objective control.•Centralized control scheme is ideal control problems with process interactions.•Multi-objective control explicitly avoids suction and congestion.•Predictive scheme pre-empts suction and congestion by early control updates.•The proposed control scheme outperformed two other controllers. 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.
ISSN:1746-8094
1746-8108
DOI:10.1016/j.bspc.2018.10.021