Improvement of Left Ventricular Assist Device (LVAD) in Artificial Heart Using Particle Swarm Optimization



In this approach, the Left ventricular assist pump for patients with left ventricular failure is
used. The failure of the left ventricle is the most common heart disease during these days. In
this article, a State feedback controller method is used to optimize the efficiency of a sampling
pump current. Particle Swarm Algorithm, which is a set of rules to update the position and
velocity, is applied to find the optimal State feedback controller parameters for the first time.
In comparison to other optimization algorithms, including genetic algorithm, PSO has higher
convergence speed. As it is shown in the simulation part in the same number of iterations, the
PSO algorithm decreases the cost function, which leads to desired transient and stability
response of the system more effectively. In addition, in this work we propose a new structure
for the cost function which includes the dynamical equations of current sampling pump in
combination with penalty sentences which decrease the speed and output fluctuations. In this
article, the system model and the system controlling parameters are set in such a way that the
proposed cost function can be optimized. The efficiency of the method is illustrated in
simulation part.