Adaptive Modeling and Control of Drug Delivery Systems Using Generalized Fuzzy Neural Networks

This chapter 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 to changes and uncertainties in these systems on line. It offers salient features, such as dynamic fuzzy neural structure, 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 chapter investigates automated regulation of Mean Arterial Pressure (MAP) through the intravenous infusion of Sodium NitroPrusside (SNP), which is one of the attractive applications in automation of drug delivery. Simulation study demonstrates superior performance of the proposed approach for estimating the drug’s effect and regulating blood pressure at a prescribed level.