Introducing an adaptive robust controller for artificial heart

Abstract

Abstract² Prolonged and uncontrolled high shear stresses and turbulence can cause hemolysis, while alternating and low-level stresses may contribute to platelet activation and thrombus formation. Such deficiencies are reported for Total Artificial Heart (TAH) systems which are generally not fully capable of dynamic adaptation to sudden pressure and volume changes. This study introduces an adaptive robust controller for a linear motor based TAH (LMTAH) which overcomes such shortcomings. Proposed controller performance is compared with simulated natural heart in normal and stressed physiological conditions. Application of adaptive robust control results in flows with less stress variation and recirculation, thereby reducing the possibility of blood clot formation and hemolysis.Keywords² Artificial heart, adaptive robust control, blood flow, blood pressure I.

Robust control of LVAD based on the sub-regional modeling of the heart

“…To solve the Riccati equation in [25], with a minimum value of , being 0.1211, P is given as: P = To demonstrate the usefulness of the parameter tuner in counteracting large parameter variations and external load disturbances, the condition with no active tuner is also presented. This is the case that the tuning parametersĴ andB of the feedback law in Eq.…”

“…And, the model is formed through a series of single blocks, which ultimately represents the entire CV system. Both the single blocks and resulting distributed model of normal heart and CV system are introduced as an appendix at the end of this manuscript [24,25].…”

“…Much like the approach given in [25], one needs to o set the variation in physical parameters and known disturbances through the usage of an adaptive control scheme. The proposed tracking controller utilizes an H1 approach as depicted in Figure 1.…”

“…where K e = [k 1 k 2 ], k 1 and k 2 are arbitrary positive constants, and v is a loop control variable. The rest of this work, including error dynamics, parameter-tunable controller, de nition of the constraints, and proof of stability of the adaptive robust controller, has been fully discussed in [25,[28][29][30][31][32][33].…”

“…By choosing a quadratic storage function, the solution of the adaptive H1 problem is built on a simple structure, suitable for digital realization. To demonstrate the functionality of the adaptive controller, and thereby the parameter tuner in counteracting large parameter variations and external disturbance, the simulated results are provided with and without the parameter tuner of the adaptive H1 controller [25].…”