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Research Papers

Disturbance Rejection in the Control of a Maglev Artificial Heart

[+] Author and Article Information
Luca Gentili

CASY-DEIS, University of Bologna, Via Risorgimento 2, 40136, Bologna, Italyl.gentili@unibo.it

Lorenzo Marconi

CASY-DEIS, University of Bologna, Via Risorgimento 2, 40136, Bologna, Italylmarconi@deis.unibo.it

Brad Paden

 University of California, Santa Barbara, CA 93106paden@engr.ucsb.edu

J. Dyn. Sys., Meas., Control 130(1), 011003 (Dec 05, 2007) (10 pages) doi:10.1115/1.2807066 History: Received February 06, 2006; Revised May 23, 2007; Published December 05, 2007

This paper is devoted to the development of an advanced controller for a maglev artificial heart: in particular, a magnetically levitated left ventricular assist device is studied and the disturbances from the natural heart are taken into account. The main goal is to define a control action able to reject dc as well as periodical disturbances from the control input in steady state. This is accomplished by exploiting the intrinsic instability of the system. The paper presents a couple of approaches for solving the problem: an internal model based approach and a solution based on adaptive observers. The internal model based solution relies on the knowledge of the frequencies of the sinusoidal disturbances affecting the system: this hypothesis is not far from the reality of the maglev apparatus as the shape and frequency of the quasiperiodic disturbance can be known with the addition of sensors. The design methodology based on the use of adaptive observers does not require the perfect knowledge of the frequencies of sinusoidal disturbances as an adaptive mechanism is presented to estimate them.

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Copyright © 2008 by American Society of Mechanical Engineers
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Figures

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Figure 1

The HeartQuest™ LVAD system

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Figure 2

HeartQuest™ LVAD with cover removed and showing blood flow path. Magnetic bearings and motor are enclosed in the impeller housing shown.

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Figure 3

Simulation with linear model; from upper to lower plot: x1, x2, u, and d

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Figure 4

Simulation with linear model with measurement noise; from upper to lower plot: x1, x2, u, and d

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Figure 5

Simulation with full nonlinear model; from upper to lower plot: x1, x2, u, and d

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Figure 6

Simulation with full nonlinear model and with measurement noise; from upper to lower plot: x1, x2, u and d

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Figure 7

Simulation with linear model; from upper to lower plot: x1, x2, u, d, and Ω̂2

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Figure 8

Simulation with linear model and measurement noise; from upper to lower plot: x1, x2, u, d, and Ω̂2

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