Minimal sensor count approach to fuzzy logic rotary blood pump flow control.

A rotary blood pump fuzzy logic flow controller without flow sensors was developed and tested in vitro. The controller, implemented in LabView, was set to maintain a flow set point in the presence of external pressure disturbances. Flow was estimated as a function of measured pump's delta P and speed, using a steady-state, nonlinear approximation. The fuzzy controller used the pump's flow estimate and delta P as feedback variables. The defuzzified control output manipulated the pump speed. Membership functions included flow error, delta P, and pump speed. Experimental runs in a mock loop (water/glycerin 3.5 cPs, 37 degrees C), using the estimated flow, were compared with those using a Transonic flow meter for nine conditions of flow and delta P (4 to 6 L/min, 150 to 350 mm Hg). Pressure disturbances generated by a servo pinch valve ranged from +/-23 to +/-47 mm Hg. Results indicated that the fuzzy controller ably regulated the flow set point to within +/-10% of the baseline even under large swings in pressure. There was no difference in controller performance between the ultrasonic flow measurement and the estimated flow calculation scenarios. These tests demonstrated that the fuzzy controller is capable of rejecting disturbances and regulating flow to acceptable limits while using a flow estimate.