Abstract
In clinical practice ventricular assist devices are generally applied with a constant rotary speed. The lack of adaptivity to changes in hemodynamic conditions might result in underpumping or suction. In this paper, a norm-optimal iterative learning control algorithm incorporating variable cycle durations is developed and tested in silico to changes in afterload, contractility, and heart rate. To simulate exercise, a fourth experiment with parallel variations of preload, afterload, contractility and heart rate is done. For this purpose, a simplified simulation model of the cardiovascular system is used. The results confirm that the algorithm is able to prevent the dilatation of the ventricle and adapt to varying cycle lengths.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
