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A control system for rotary ventricular assist devices was developed to automatically regulate the pumping speed of the device to avoid ventricular suction. The control system comprises a suction detector and a fuzzy logic controller (FLC). The suction detector can correctly classify pump flow patterns, using a discriminant analysis (DA) model that combines several indices derived from the pump flow signal, to classify the pump status as one of the following: no suction (NS), moderate suction (MS), and severe suction (SS). The discriminant scores, which are the output of the suction detector, were used as inputs to the FLC. Based on this information, the controller updates pump speed, providing adequate flow and pressure perfusion to the patient. The performance of the control system was tested in simulations over a wide range of physiological conditions, including hypertension, exercise, and strenuous exercising for healthy, sick, and very sick hearts, using a lumped parameter model of the circulatory system coupled with a left ventricular assist device. The controller was able to maintain cardiac output and mean arterial pressure within acceptable physiologic ranges, while avoiding suction, demonstrating the feasibility of the proposed control system.