A centralized multi-objective model predictive control for a biventricular assist device: An in silico evaluation
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) algori...
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| Format: | Article |
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Elsevier
2019
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| author | Koh, Vivian Ci Ai Ho, Yong Kuen Stevens, Michael Charles Ng, Boon Chiang Salamonsen, Robert Francis Lovell, N.H. Lim, Einly |
| author_facet | Koh, Vivian Ci Ai Ho, Yong Kuen Stevens, Michael Charles Ng, Boon Chiang Salamonsen, Robert Francis Lovell, N.H. Lim, Einly |
| author_sort | Koh, Vivian Ci Ai |
| collection | UM |
| description | 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. |
| first_indexed | 2024-03-06T05:50:02Z |
| format | Article |
| id | um.eprints-20045 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:50:02Z |
| publishDate | 2019 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | um.eprints-200452019-01-17T04:42:25Z http://eprints.um.edu.my/20045/ A centralized multi-objective model predictive control for a biventricular assist device: An in silico evaluation Koh, Vivian Ci Ai Ho, Yong Kuen Stevens, Michael Charles Ng, Boon Chiang Salamonsen, Robert Francis Lovell, N.H. Lim, Einly R Medicine 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. Elsevier 2019 Article PeerReviewed 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 <https://doi.org/10.1016/j.bspc.2018.10.021>. https://doi.org/10.1016/j.bspc.2018.10.021 doi:10.1016/j.bspc.2018.10.021 |
| spellingShingle | R Medicine Koh, Vivian Ci Ai Ho, Yong Kuen Stevens, Michael Charles Ng, Boon Chiang Salamonsen, Robert Francis Lovell, N.H. Lim, Einly A centralized multi-objective model predictive control for a biventricular assist device: An in silico evaluation |
| title | A centralized multi-objective model predictive control for a biventricular assist device: An in silico evaluation |
| title_full | A centralized multi-objective model predictive control for a biventricular assist device: An in silico evaluation |
| title_fullStr | A centralized multi-objective model predictive control for a biventricular assist device: An in silico evaluation |
| title_full_unstemmed | A centralized multi-objective model predictive control for a biventricular assist device: An in silico evaluation |
| title_short | A centralized multi-objective model predictive control for a biventricular assist device: An in silico evaluation |
| title_sort | centralized multi objective model predictive control for a biventricular assist device an in silico evaluation |
| topic | R Medicine |
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