Neuro-Fuzzy Controller Design for Left Ventricular Assist Device Speed Regulation
DOI:
https://doi.org/10.31185/wjes.Vol14.Iss3.998Keywords:
LVAD, cardiovascular system, control parameter, neural network, fuzzyAbstract
The mechanical Left Ventricular Assist Device (LVAD) has become an important therapeutic device for patients with advanced heart failure. However, regulating LVAD pump speed under varying physiological conditions remains challenging due to the nonlinear and time-varying nature of the cardiovascular system (CVS). In this study, the CVS is represented using a lumped-parameter state-space model of the left ventricle derived from a nonlinear equivalent circuit. A model-free Neural Network PID (NN-PID) controller integrated with a fuzzy inference system is proposed for LVAD speed regulation. The NN-PID controller enables model-free pump speed control, while the fuzzy inference system adaptively tunes the controller parameters to accommodate changes in physiological conditions. Simulation results demonstrate that the proposed NN-PID controller improves pump-flow tracking accuracy and maintains the pump flow within an approximately physiological range of 1–4 L/min under varying operating conditions. The proposed controller also exhibits improved adaptability compared with the open-loop LVAD system.
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