Adaptive fuzzy neural control of mean arterial pressure through sodium nitroprusside infusion

This paper presents an adaptive modeling and control scheme for drug delivery systems based on a generalized fuzzy neural network (G-FNN). The proposed G-FNN is a novel intelligent modeling tool, which can model the unknown nonlinearities of complex drug delivery systems and adapt on line to changes and uncertainties in these systems. It offers salient features, such as dynamic fuzzy neural topology, fast online learning ability and adaptability, etc. System approximation formulated by the G-FNN is thus employed in the adaptive controller design for drug infusion. In particular, this paper investigates the automated regulation of mean arterial pressure (MAP) through the intravenous infusion of sodium nitroprusside (SNP), which is atypical application in automation of drug delivery. Simulation study demonstrates the ability of the proposed approach for estimating the drug's effect and regulating blood pressure at a prescribed level.