A centralized multi-objective model predictive control for a biventricular assist device: An in silico evaluation. (March 2019)

• Record Type: Journal Article
• Authors: Koh, V.C.A.; Ho, Y.K.; Stevens, M.C.; Ng, B.C.; Salamonsen, R.F.; Lovell, N.H.; Lim, E.
• Is Part Of: Biomedical signal processing and control. Volume 49(2019)
• Page Start: 137
• Page End: 148
• Publication Date: 2019-03
• Subjects: Frank-Starling (FS) mechanism -- Physiological control -- Ventricular suction -- Vascular congestion; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2018.10.021
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: 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. 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.