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

Content Provider	IEEE Xplore Digital Library
Author	Yang Gao Meng Joo Er
Copyright Year	2003
Description	Author affiliation: Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore (Yang Gao; Meng Joo Er)
Abstract	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.
Sponsorship	Honeywell Lab. Xerox Nat. Instruments Math Works
Starting Page	2198
Ending Page	2203
File Size	453383
Page Count	6
File Format	PDF
ISBN	0780379241
ISSN	01912216
DOI	10.1109/CDC.2003.1272944
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-12-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Programmable control Adaptive control Fuzzy control Pressure control Blood pressure Drug delivery Fuzzy neural networks Uncertainty Nonlinear dynamical systems Network topology
Content Type	Text
Resource Type	Article

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