Adaptive control strategy for blood pressure regulation using a fuzzy neural network

This paper presents an adaptive fuzzy neural control strategy to regulate Mean Arterial Pressure (MAP) through the intravenous infusion of Sodium NitroPrusside (SNP). The proposed indirect adaptive controller involves a feedforward Generalized Fuzzy Neural Network (G-FNN) together with a linear feedback loop. It is capable of achieving real-time fine control under significant uncertainties and without any prior knowledge of the system dynamics. This is achieved through adaptive learning and modeling of the system dynamics and its uncertainties based on the G-FNN. Salient features of the proposed G-FNN include dynamic fuzzy neural structure, fast online learning ability and adaptability, etc. Simulation studies demonstrate the superior performance of the proposed approach for estimating the drug's effect and regulating blood pressure at a prescribed level.