Recursive estimation of systemic arterial parameters for control of an electrically actuated total artificial heart

A method for recursively estimating the parameters of a model of the systemic arterial bed for control of an electrically actuated total artificial heart (TAH) has been developed and tested. The parameters have physical meaning and are estimated on the basis of noninvasive measurement of aortic flow and pressure during systole. The performance of the estimation algorithm was tested on data generated by two different models of the systemic arterial bed, using normal canine parameters. Results demonstrate the ability of the estimator to converge quickly and to track time-varying parameters